From Zero-COVID to Global Alignment: Transnational Pressures and China’s Pandemic Communication Transformation

From Zero-COVID to Global Alignment: Transnational Pressures and China’s Pandemic Communication Transformation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report From Zero-COVID to Global Alignment: Transnational Pressures and China’s Pandemic Communication Transformation Liu Dandan, Siti Ezaleila Binti Mustafa, NOR ZALIZA BINTI SARMITI This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7117519/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Nov, 2025 Read the published version in Globalization and Health → Version 1 posted 8 You are reading this latest preprint version Abstract The COVID-19 pandemic radically reshaped global communication dynamics, compelling governments to deliver frequent updates on infection rates, public health protocols, and evolving scientific knowledge. This study examines how the Chinese government, through its official press conferences, established and maintained specific frames during the COVID-19 pandemic across four distinct phases from 2020 to 2023. Using Latent Dirichlet Allocation (LDA) topic modeling on 154 press conference transcripts, we identified seven distinct communication frames. The analysis reveals a sophisticated cyclical frame reinforcement model that challenges traditional linear crisis communication theories, demonstrating how authoritarian communication systems can strategically reactivate previously effective frames for new policy objectives. The study contributes to crisis communication theory by identifying semantic governance as a distinctive mechanism for maintaining regime legitimacy during major policy transitions, enabling governments to transform policy reversals into adaptive evolution through strategic linguistic engineering. Crisis Communication Framing Theory COVID-19 Government Communication Topic Modeling Pandemic Response Figures Figure 1 Introduction The COVID-19 pandemic radically reshaped global communication dynamics, compelling governments to deliver, requiring governments to provide frequent updates on infection rates, public health protocols, and evolving scientific knowledge (Seeger 2006). As the crisis unfolded in real time, one of the most visible and routine channels for official announcements became the government press conference. From the early stages of the outbreak in Wuhan, China, to similar practices in other nations, press conferences rapidly assumed a pivotal role in distributing accurate information on the epidemiological situation, clarifying preventive measures, and addressing public concerns regarding disruptions to daily life and economic stability (Kim and Kreps 2020; Kneuer and Wallaschek 2023). By providing a centralized platform for government spokespersons, health authorities, and occasionally scientific experts, these events aimed to instill confidence, coordinate policy responses, and guide public behaviors in an atmosphere rife with uncertainty. A central advantage of official or government press conferences is the projection of unified, authoritative messaging (MacKay et al. 2022). In high-stakes crises such as COVID-19, citizens expect clear guidelines about mask usage, social distancing, testing, and eventual vaccination. Press conferences permit government officials to present this guidance as a coherent narrative, reducing discrepancies that might otherwise arise if multiple agencies or ministries were to communicate independently. This consolidated approach can lessen confusion, maintain institutional legitimacy, and ensure that policy changes —such as new travel restrictions or amendments to quarantine durations— are presented as part of an organized governmental strategy (Seeger 2006). In China, for instance, regular briefings by the Joint Prevention and Control Mechanism at the State Council sought to demonstrate unwavering focus and swift decision-making in the face of fluctuating daily case counts and variant threats (He, Shi, and Liu 2020). Moreover, press conferences allow a formal mechanism for media representatives to question officials and obtain clarifications, albeit within certain procedural constraints (Dau and Ellis 2023). This interplay, even if sometimes constrained, can foster a veneer of transparency: when officials publicly address challenges, it indicates accountability to the populace. Insofar as reporters are permitted to probe policy rationales, these interactions can reveal strategic priorities, from procurement of medical supplies to economic stimulus for pandemic-hit industries. As a result, press conferences function as communicative "gateways" through which the public can glean at least a portion of the rationale behind policy moves (Chan and Fung 2021). Framing and Its Impact on Public Understanding Framing, fundamentally, is the process of selecting certain aspects of reality and making them more salient in a communication text, in order to define problems, diagnose causes, make moral judgments, or propose remedies (Entman 1993). In the context of a global health emergency, where the stakes include public compliance and individual safety, how government spokespersons frame” a topic can significantly influence how citizens interpret both the severity of the crisis and the viability of proposed solutions (Chong and Druckman 2007). For instance, by framing COVID-19 as a war” (Benziman 2020), leaders can invoke urgency and unity, shaping the public’s willingness to accept stringent measures. Conversely, a frame that overly normalizes the situation may prompt complacency or insufficient adherence to guidelines (Harper et al. 2021). Press conferences are particularly potent sites for framing because they often represent the first authoritative source of information on policy shifts or critical health data (Seeger 2006). The rhetorical choices employed—whether acknowledging uncertainties, highlighting successes, or calling for civic duty—can reinforce specific narratives that trickle down into mainstream media reporting and user-generated content on social media (Zhou et al. 2021). In effect, these official statements set the initial interpretive framework or "top-down frames" for broader public discourse. Journalists rely on quotes and figures from these briefings, which can then be adapted or critiqued in editorials and news coverage, while social media users may echo or dispute the official terminology, adding emotional or personal perspectives (Chen et al. 2020). Thus, the frames introduced in press conferences play a foundational role in shaping subsequent information flows across multiple communication channels. Aim and Research Questions Building on the observations above, this study sets out to analyze how the Chinese government, through its official press conferences, established and maintained specific frames during the COVID-19 pandemic. The objective is to examine government framing strategies in official COVID-19 press conferences and their evolution over time. The study raises three core research questions: RQ1: What predominant frames characterize Chinese government COVID-19 press conferences, especially in relation to epidemic control, vaccination, economic recovery, and other salient themes? RQ2: In what ways did these Chinese governmental communication frames evolve over different phases of the pandemic—from the initial outbreak to peak crisis management and eventual easing of restrictions—and what factors prompted these shifts? RQ3: What role did the Chinese government’s public health messaging play in managing the COVID-19 pandemic, including fostering compliance, reassuring citizens, and addressing misinformation or emotional anxieties? By systematically analyzing the press conference transcripts, this study aims to advance crisis communication theory by examining both the temporal dynamics of frame evolution and the mechanisms of authoritarian crisis discourse. This macro-level perspective is essential because it sets the baseline framework that official media outlets subsequently refine in their coverage, and that citizens on social media endorse or contestfor media coverage and public discourse (Lyu, Arif, and Shahrin 2024). Moreover, adopting a longitudinal approach—tracking frames from early 2020 through early 2023—allows for insight intoshows how crisis communication adapts to changing epidemiological and sociopolitical conditions. It acknowledges that what a government emphasizes at the outbreak stage may differ substantially from what it underscores amid vaccination rollouts or when loosening restrictions for social and economic normalcy. Focusing on government press conferences also taps into prior research in crisis communication studies that underscores the performative element of official addresses (Seeger 2006). Press conferences serve not only to transmit facts but also to display governmental competence, reassure the public, and maintain national unity (Chan and Fung 2021). Hence, understanding the interplay of factual announcements, emotional appeals, and strategic justifications within these briefings gives researchers a window intoprovides insight into how leadership navigates and constructs crisis narratives. (Entman 1993; Goffman 1974) alongside topic modeling (Maier et al. 2021) to generate both a quantitative mapping of emergent themes and a qualitative interpretation of how these themes function as frames.to produce a quantitative mapping of themes and a qualitative interpretation of frames Literature Review This section provides an expanded and more analytical discussion of framing theory in government communication, empirical research on government discourse during health crises, and the relevance of topic modeling techniques. In response to prior critiques, the text below integrates a comparative perspective on authoritarian versus democratic systems, incorporates the crisis communication phases proposed by (Coombs and Holladay 2014), and explores framing subcategories—such as episodic vs. thematic, and gain vs. loss frames—to assess their potential impact on public trust and compliance. Framing Theory and Government Communication Framing theory underscores how communicative actors—government leaders, spokespersons, and agencies—select and emphasize certain aspects of an issue to shape public perception and guide responses (Entman 1993; Chong and Druckman 2007). At its core, framing is about organizing meaning, highlighting particular narratives or dimensions of a phenomenon while omitting others, thus steering how the audience interprets events and what solutions they see as appropriate. organizes meaning by emphasizing certain aspects and omitting others, steering how audiences interpret events and identify solutions (Goffman 1974). In crisis contexts like pandemics, the urgency and high stakes of public health measures mean that framing becomes a pivotal tool for governments to generate trust, cooperation, and rapid behavior change (Seeger 2006). However, governments do not all frame crises in the same way, as political systems significantly influence both the style and content of official messages. In authoritarian regimes, where information flows are more centrally controlled, top-down directives and nationalistic frames can dominate. Government communications might emphasize collective duty and heroic narratives of frontline workers, invoking unity and portraying any dissent as undermining societal well-being (Benziman 2020). Conversely, democratic governments often contend with pluralistic media environments and must negotiate policy framing with diverse stakeholders. While they, too, may use moral imperatives and metaphors—such as the “war on COVID-19”—the presence of an active free press and opposition parties can foster competing frames that highlight potential policy failures or trade-offs. While democratic governments may also use “war” metaphors, an active free press and opposition parties foster competing frames highlighting policy failures or trade-offs (Chong and Druckman 2007).. Building on frame evolution theory, governments adjust their framing as a crisis progresses through different stages. (Coombs and Holladay 2014) delineates crisis communication phases: pre-crisis, acute crisis, and post-crisis. In pandemics, the pre-crisis phase often involves warnings or minimal communications designed to alert the public without causing alarm. The acute phase features intensified messaging focusing on urgent measures—social distancing, lockdowns, or vaccination. The post-crisis phase typically shifts attention to recovery, rebuilding trust, and mitigating long-term impacts. Within each phase, frames may evolve, moving from a “war metaphor” emphasizing threat and urgency to more thematic frames centering on societal recovery or collective resilience. Framing subcategories also merit attention due to their influence on public trust and compliance. For example, episodic framing personalizes the crisis through individual stories, aiming to elicit empathy or fear, while thematic framing places the crisis in broader structural or policy contexts (Chong and Druckman 2007). Governments can also employ gain vs. loss frames to highlight either the benefits of compliance (e.g., protecting vulnerable populations) or the dire consequences of non-compliance (e.g., increased mortality rates). Research in health communication suggests that gain-framed messages can enhance public compliance by emphasizing positive outcomes, whereas loss-framed messages may provoke fear but risk alienating certain segments of the audience (Dada et al. 2021). Balancing these sub-framing strategies is crucial to maintaining both credibility and public cooperation. In sum, framing theory provides a conceptual lens for evaluating how governments in different political contexts structure their crisis narratives. Whether through war metaphors, duty-based appeals, or economic recovery frames, these communicative choices shape how citizens perceive their responsibilities and how they respond in real time perceive their responsibilities and respond. In pandemics, effective framing not only informs the public but also motivates collective action—whether by fostering trust in authoritarian settings with centralized messaging or by navigating complex media ecosystems in democratic environments. Empirical Research on Government Discourse in Crises Empirical studies of government framing in public health emergencies—SARS, Ebola, Zika, and COVID-19—reveal that political system type, cultural context, and the crisis stage significantly affect official messaging (Kim and Kreps 2020). In authoritarian contexts, messages tend to highlight the protective role of the state and the importance of public obedience, often combined with thematic frames of collective struggle (Huang et al. 2020). During the 2003 SARS outbreak, for instance, Chinese government communications evolved from limited, guarded reports to more proactive disclosures under international scrutiny, illustrating a strategic adaptation in framing (Gui 2021; Ning et al. 2021). Meanwhile, Western democracies addressing the same crisis had to balance transparency against potential overreaction, with leaders often facing critical media queries that complicated a singular, unified frame. The Ebola crisis in West Africa further demonstrates how local beliefs and cultural practices influence government frames. Official discourse in Liberia and Sierra Leone centered on moral appeals for compliance with quarantine measures, invoking communal duty and respect for the deceased (Jacobsen et al. 2016). In Western countries—less directly affected—the frame shifted toward preventing imported cases, emphasizing border control and biomedical interventions. These divergent emphases underscore how episodic story-based appeals (e.g., accounts of individual Ebola victims) coexisted with thematic messages (e.g., societal or international cooperation), and how local authorities navigated tension between public health directives and deeply held cultural rituals (Dada et al. 2021). With COVID-19, research has documented further variations in government discourse across political systems. Authoritarian leaders often leveraged “war metaphors” early in the pandemic, using centralized daily briefings to communicate strict lockdown policies and mobilize national solidarity (Benziman 2020). Democratic leaders also invoked war-like rhetoric, but faced more scrutiny from media outlets, opposition parties, and health experts; in these settings, alternative frames—focusing on economic relief, social welfare, or the moral imperative to protect vulnerable populations—emerged alongside official statementsbut faced greater scrutiny, and alternative frames (economic relief, social welfare, protecting vulnerable populations) emerged alongside official narratives (Kneuer and Wallaschek 2023).. As the pandemic wore on, many governments shifted from acute-crisis framing (lockdowns, strict measures) to recovery-oriented frames emphasizing resumption of economic and social activitiesa return to normalcy (Bernard et al. 2021). These phased transitions align with (Coombs and Holladay 2014)’s crisis communication lifecycle, as governments refined their narratives to maintain public compliance while restoring normalcyrestoring stability. Despite considerable case studies, systematic analyses of official press conference transcripts remain relatively scarce. Scholars have often relied on policy documents or media reports, potentially overlooking the real-time rhetorical strategies officials use. Yet press conferences are pivotal events where governments disclose new data, address rumors, and reinforce compliance norms (Chapman and Miller 2020). Relevance of LDA and Topic Modeling Given the extensive volume of text generated in government press conferences—especially over a multi-year pandemic—researchers increasingly employ computational techniques like Latent Dirichlet Allocation (LDA) to identify and track recurring themes. LDA is a probabilistic model that infers hidden patterns from word co-occurrence, dividing a corpus into thematically cohesive “topics” (Blei, Ng, and Jordan 2003; Maier et al. 2021). This approach offers three major advantages in analyzing pandemic-related government discourse: First, press conferences can produce millions of words, making purely manual coding impractical (Xie, Xue, and Zhao 2022). LDA automates the initial categorization of content, highlighting prominent themes—such as lockdown measures, vaccination campaigns, or economic relief. Second, LDA’s data-driven grouping can reveal unexpected patterns or sub-themes that might be missed if researchers impose predefined coding categories (Jacobs and Tschötschel 2019). It thus serves as a check against researcher bias, ensuring that the data itself guides the identification of salient topics. Third, LDA can be applied to different crisis phases (Coombs and Holladay 2014), detecting how topics emerge, evolve, or vanish over time (Blei 2012). This is critical in comparing responses between authoritarian and democratic settings, or in noting how frames shift from “immediate threat” to “recovery” emphasis. However, LDA alone cannot fully capture the nuances of framing. Topics identified by the model may cluster around high-frequency terms like “mask,” “vaccine,” or “economic relief,” but may overlook subtler discursive devices such as metaphors, moral imperatives, or the interplay between episodic and thematic framing. For instance, “war metaphors” may not coalesce around a single keyword; instead, they arise from repeated references to “fight,” “victory,” “battle,” and “frontline heroes” (Benziman 2020). Detecting gain vs. loss frames similarly requires close attention to how governments articulate outcomes (e.g., “preventing deaths” vs. “facing escalating fatalities”). Consequently, mixed-method approaches are recommended (Chong and Druckman 2007; Xie, Xue, and Zhao 2022). After LDA identifies the main topics, researchers can conduct qualitative frame analysis of specific segments, examining rhetorical elements—such as moral appeals, emotional tone, or policy justifications—to interpret how framing shapes public trust and compliance (Watkins and Clevenger 2021). This dual strategy ensures that researchers capture both macro-level patterns and the micro-level discursive strategies that underpin those patterns. For the present study, focusing on Chinese government press conferences, LDA can reveal the shifting emphases—ranging from disease containment to economic revival—across various COVID-19 phases. A subsequent manual or semi-automatic review can then map these topic clusters onto recognized frames—like “war metaphors,” “solidarity appeals,” or “economic recovery.” By incorporating episodic vs. thematic and gain vs. loss framing dimensions, the analysis can further elucidate how a centralized, authoritarian communication apparatus evolves its narrative over time to maintain legitimacy, manage public sentiment, and encourage compliance. This combined approach aligns with foundational insights from framing theory (Entman 1993; Goffman 1974) and accounts for the contextual and dynamic nature of crisis communication (Coombs and Holladay 2014). Ultimately, it offers a more comprehensive view of how government discourse shapes, and is shaped by, public perceptions throughout a protracted global health emergency. Methodology Research Design and Theoretical Framework This study employs a longitudinal, mixed-methods approach to analyze how transnational pressures influenced China’s pandemic communication transformation from zero-COVID policies to global alignment strategies between February 2020 and February 2023. The research design integrates computational text analysis with qualitative framing theory to examine how globalization processes shaped public health communication strategies during an unprecedented global health crisis (Labonté, Mohindra, and Schrecker 2011). The theoretical framework draws upon globalization and health scholarship that emphasizes how transnational dynamics influence domestic health policy communication, particularly in contexts where national health systems must navigate between domestic priorities and international pressures (Kickbusch et al. 2013). The methodological approach recognizes that pandemic communication represents a critical intersection between global health governance and national crisis management, where communication strategies reflect broader tensions between sovereignty and interdependence in global health systems (Moon, Røttingen, and Frenk 2017). Press conferences serve as particularly valuable sites for analyzing these dynamics because they function as primary channels through which governments articulate their positioning within global health governance frameworks while addressing domestic constituencies. The longitudinal design enables examination of how communication strategies evolved in response to changing international contexts, including World Health Organization policy shifts, international travel restrictions, vaccine diplomacy initiatives, and global economic pressures. The research adopts a phase-based analytical framework that aligns with established crisis communication models while incorporating insights from globalization and health literature regarding policy adaptation under transnational pressure (Coombs and Holladay 2014; Labonté, Mohindra, and Schrecker 2011). This approach acknowledges that crisis communication in globalized contexts involves continuous negotiation between domestic imperatives and international expectations, with communication strategies serving as mechanisms for managing these competing pressures. The temporal segmentation enables detailed analysis of how specific transnational factors—including international criticism, economic interdependence, and global health governance expectations—influenced communication frame evolution across different pandemic phases. This study adopts a longitudinal mixed-methods design (combining topic modeling and framing analysis) to examine how transnational pressures shaped China’s pandemic press conference communication from the initial outbreak through the policy alignment in 2023. It integrates computational text analysis with framing theory, situating pandemic communication at the nexus of global health governance and domestic crisis management. The approach aligns with crisis phase models (Coombs and Holladay 2014) and draws on globalization scholarship (Labonté, Mohindra, and Schrecker 2011), allowing us to track how international criticism, economic interdependence, and global health governance expectations influenced the evolution of official frames over time. Data Collection and Corpus Construction The study corpus comprises 154 official press conference transcripts from China’s State Council Joint Prevention and Control Mechanism, representing the complete record of central government COVID-19 communication throughout the study period. These transcripts were systematically collected from the official Chinese government website (Gov.cn) using automated extraction protocols that ensured comprehensive coverage while maintaining data integrityusing automated extraction to ensure comprehensive coverage. The selection of central government communications reflects the study’s focus on how national-level authorities navigate transnational pressures in global health contexts, as opposed to local implementation dynamics focuses on national-level communications to capture transnational influence, rather than local-level messaging. The corpus construction strategy prioritized institutional consistency and policy authority by focusing exclusively on the State Council Joint Prevention and Control Mechanism, which served as China’s primary coordination body for pandemic response and international engagement. This institutional focus ensures analytical coherence while capturing communications most directly influenced by transnational pressures, including international criticism of early pandemic response, global vaccine distribution negotiations, and international economic recovery coordination. The resulting dataset comprises approximately 16.9 million Chinese characters, equivalent to 2.9 million word tokens following segmentation, providing substantial textual depth for computational analysis. Temporal coverage spans from February 2020 through February 2023, encompassing the complete cycle of China’s pandemic response from initial outbreak management through policy normalization. This timeframe captures critical periods of international engagement and policy adjustment, including early international criticism and transparency pressures, global vaccine development competition, international travel restriction negotiations, and eventual alignment with global endemic management approaches. The comprehensive temporal scope enables analysis of how sustained transnational pressures influenced long-term communication strategy evolution rather than merely short-term tactical adjustments. Data collection protocols incorporated quality assurance measures to ensure textual accuracy and completeness. Automated extraction targeted official statements, expert responses, and journalist questions while excluding non-textual elements that might introduce analytical noise. The extraction process maintained respectful crawling frequencies in accordance with website usage policies while ensuring comprehensive coverage of all available transcripts. Post-collection verification procedures confirmed that the corpus represents a complete census of central government COVID-19 communications during the study period, providing maximum representativeness for analyzing official discourse evolution. Temporal Segmentation and Phase Definition The corpus was segmented into four distinct phases based on major policy milestones and international developments that reflected changing transnational pressures and global health governance dynamics. This segmentation strategy enables comparative analysis of how communication frames evolved in response to specific international contexts and transnational influences throughout the pandemic timeline. The International Scrutiny Phase (January-March 2020) encompasses the period of intense international attention and criticism regarding China’s initial pandemic response, including World Health Organization investigations, international media scrutiny, and diplomatic tensions over transparency and information sharing. This phase captures communication strategies developed under unprecedented international pressure for accountability and transparency in global health emergency contexts. Government discourse during this period reflected attempts to balance domestic crisis management with international reputation management and diplomatic relationship preservation. The Global Cooperation Phase (April 2020-February 2021) marks the transition toward international collaboration and competitive positioning in global vaccine development and distribution networks. This phase encompasses China’s engagement with global vaccine diplomacy initiatives, participation in international research collaboration, and positioning within global health governance frameworks. Communication strategies during this period reflect attempts to demonstrate international leadership while maintaining domestic policy autonomy, particularly regarding vaccine development sovereignty and distribution priorities. The International Isolation Phase (March 2021-November 2022) coincides with growing international criticism of zero-COVID policies and increasing economic and diplomatic pressures for policy alignment with global approaches. This phase captures communication strategies developed in response to international travel restrictions, economic isolation pressures, and diplomatic tensions over pandemic policy divergence. Government discourse increasingly emphasized policy justification and sovereignty protection while managing growing international pressure for policy convergence. The Global Alignment Phase (December 2022-February 2023) represents the period of rapid policy convergence with international approaches following sustained transnational pressure and economic imperatives. This phase encompasses the dramatic policy reversal toward endemic management approaches that aligned with global health governance recommendations and international economic integration requirements. Communication strategies during this period reflect efforts to frame policy changes as adaptive evolution rather than external capitulation while maintaining regime legitimacy throughout the transition. Computational Text Analysis and Topic Modeling The study employs Latent Dirichlet Allocation (LDA) topic modeling to systematically identify and track thematic patterns across the extensive corpus, enabling analysis of how transnational pressures influenced communication frame evolution over time (Blei, Ng, and Jordan 2003). This computational approach provides objective identification of recurring themes while enabling temporal analysis of frame prominence and evolution across different phases of international engagement. The methodology integrates computational rigor with qualitative interpretation to capture both broad patterns and nuanced shifts in communication strategies. Text preprocessing procedures incorporated Chinese language-specific considerations, including segmentation using Jieba tokenization, removal of function words and boilerplate language, and consolidation of synonymous terms to minimize semantic fragmentation. The preprocessing pipeline maintained semantic integrity while optimizing the corpus for computational analysis, ensuring that identified topics reflect genuine thematic patterns rather than linguistic artifacts. Quality control measures included manual review of preprocessing outcomes and iterative refinement to optimize topic coherence and interpretability. Model specification involved systematic optimization of hyperparameters through iterative testing of topic numbers (K) ranging from 5 to 25, with selection based on coherence metrics and qualitative interpretability assessments. The final model specification (K=8) balanced computational coherence with theoretical meaningfulness, ensuring that identified topics align with (coherence score: 0.56) broader crisis communication themes. Frame Analysis and Theoretical Integration The study integrates computational topic identification with established framing theory to analyze how transnational pressures influenced communication strategy evolution throughout the pandemic. Frame analysis follows Entman’s conceptual framework, examining how topics function to define problems, diagnose causes, make moral evaluations, and suggest remedies within the context of global health governance and transnational pressure management (Entman 1993). This integration enables analysis of both manifest content patterns and latent strategic functions of communication frames. Topic-to-frame mapping procedures involved systematic evaluation of computational topics against established crisis communication frame categories, with particular attention to how frames reflect transnational influence and global health governance positioning. Two independent researchers conducted preliminary mappings based on topic vocabulary and theoretical alignment, achieving 75% initial consensus with structured discussion resolving remaining disagreements. External validation by three additional experts yielded 83.3% agreement with final mappings, providing confidence in interpretive validity. The analytical framework incorporates insights from globalization and health scholarship regarding how transnational pressures influence domestic health policy communication, particularly focusing on sovereignty-interdependence tensions and legitimacy management strategies (Kickbusch et al. 2013; Labonté, Mohindra, and Schrecker 2011). Frame analysis examines how communication strategies navigate between domestic audience expectations and international pressure management, with particular attention to how frames evolve in response to changing transnational contexts and global health governance dynamics. Temporal frame analysis tracks how specific frames emerge, evolve, and decline across different phases of international engagement, enabling identification of communication adaptation patterns in response to transnational pressures. The methodology examines both frame content evolution and strategic function shifts, analyzing how similar thematic content serves different strategic purposes across different international contexts. This approach enables nuanced understanding of how globalization processes influence crisis communication strategies in complex political and health system contexts. The validation framework ensures methodological rigor through multiple verification procedures. Internal validation employs coherence metrics and stability testing to confirm computational reliability, while external validation compares results against independent data sources including policy documents and press conference titles. Expert consensus procedures provide additional verification of interpretive validity, ensuring that frame mappings reflect genuine theoretical alignment rather than analytical artifacts. This multi-layered validation approach strengthens confidence in findings while maintaining transparency regarding methodological limitations and assumptions. Ethical Considerations and Data Availability All data analyzed in this study consists of publicly available government communications, eliminating privacy concerns and ensuring compliance with research ethics standards. The press conference transcripts represent official government statements intended for public dissemination, with no personal or sensitive information requiring protection. The study methodology focuses exclusively on publicly available textual content, with no human subjects involvement or private data collection. Data collection procedures adhered to website usage policies and maintained respectful crawling frequencies to avoid disrupting official government websites. The automated extraction protocols incorporated appropriate delays and access limitations to ensure responsible data collection practices. All extracted content remains publicly accessible through official government channels, with the study corpus serving as a systematic compilation rather than creating new data accessibility issues. The complete dataset and analytical code are available for replication and verification purposes, supporting transparency and reproducibility in computational social science research. Documentation includes detailed preprocessing procedures, model specifications, and validation protocols to enable independent verification of findings. This commitment to open science practices aligns with contemporary standards for computational text analysis research while respecting the public nature of the analyzed communications. Corpus Overview by Transnational Pressure Response Phases Phase No. of Press Conferences Date Range Approx. Tokens (millions) International Scrutiny Phase 35 Jan–Mar 2020 0.52 Global Cooperation Phase 42 Apr 2020–Feb 2021 0.89 International Isolation Phase 53 Mar 2021–Nov 2022 1.06 Global Alignment Phase 24 Dec 2022–Feb 2023 0.43 Total 154 Jan 2020–Feb 2023 2.90 LDA Model Validation Results Validation Method Description Outcome Coherence Score Statistical measure of topic coherence 0.56 (for K=8 model) Stability Testing Repeated model runs to check topic stability High overlap in top terms across runs Expert Review Domain experts validate topic-to-frame mapping 83.3% agreement External Comparison Compare topics with policy documents Topics aligned with policy themes Example of Topic-to-Frame Mapping Topic (LDA Keywords) Interpreted Frame Lockdown, quarantine, travel, restrictions, control Containment Measures Frame Vaccine, dose, develop, trial, supply Vaccination Campaign Frame Economy, market, jobs, reopen, stimulus Economic Relief/Recovery Frame Results Transnational Communication Framework Evolution The LDA analysis of 154 Chinese government COVID-19 press conferences (February 2020-February 2023) identified seven distinct communication frames that evolved systematically in response to transnational pressures and global health governance expectations. This longitudinal analysis reveals how China’s pandemic communication transformed from domestic crisis management to strategic global alignment, demonstrating sophisticated navigation of sovereignty-interdependence tensions in global health contexts. Seven Communication Frames and Global Health Context Frame Frame Name Global Health Governance Context Prominence (%) Table 4 (Continued) Frame Frame Name Global Health Governance Context Prominence (%) (Continued on next page) Transnational Health Governance Official communication emphasizing integration with WHO frameworks, international cooperation protocols, and global health security contributions 4.5 2 Economic-Health Nexus Enterprise support and economic recovery within global supply chain interdependence, balancing domestic stability with international trade pressures 14.2 3 Healthcare System Resilience Comprehensive health service delivery demonstrating system capacity to domestic audiences while signaling health system strength to international observers 27.6 4 Global Epidemiological Standards Case reporting and surveillance aligned with international transparency expectations, data sharing responding to global governance demands 16.7 5 Vaccine Diplomacy Balance Vaccine development emphasizing technological sovereignty while engaging global distribution networks and international cooperation initiatives 15.3 6 Adaptive Policy Convergence Prevention and control measures evolving toward international best practices under sustained transnational pressure for policy alignment 13.8 7 Global Supply Chain Integration Logistics coordination within international health security frameworks, managing domestic needs with global economic interdependence 8.9 Phase-Specific Transnational Pressure Response Patterns The analysis reveals systematic frame evolution across four phases, each characterized by distinct transnational pressure dynamics and corresponding communication adaptations that reflect China’s strategic navigation between domestic legitimacy and international expectations. International Scrutiny Phase (January-March 2020): Healthcare System Resilience and Global Epidemiological Standards dominated as China faced unprecedented international criticism regarding transparency and accountability in global health emergency response. Communication strategy emphasized demonstrating state capacity to international observers while establishing data reporting systems aligned with WHO expectations. The government deployed 35 press conferences during this phase, representing the highest communication intensity, as authorities sought to counter international criticism while maintaining domestic crisis management credibility. Frame deployment during this phase reflected classic sovereignty protection strategies under international pressure. Healthcare System Resilience messaging (45% of communication content) emphasized medical system capacity and professional competence to counter international criticism of initial response delays. Global Epidemiological Standards messaging (25%) focused on establishing transparent reporting mechanisms aligned with international surveillance expectations, demonstrating China’s integration with global health governance frameworks despite sovereignty concerns. Global Cooperation Phase (April 2020-February 2021): Vaccine Diplomacy Balance and Economic-Health Nexus emerged prominently as China positioned itself as a responsible global health actor while maintaining domestic policy autonomy. This phase encompassed 42 press conferences emphasizing China’s contributions to global vaccine development and distribution networks. Communication strategy balanced international cooperation messaging with technological sovereignty assertions, reflecting strategic navigation between global integration and domestic legitimacy requirements. Vaccine Diplomacy Balance messaging (35%) emphasized China’s scientific achievements and international cooperation contributions, positioning domestic vaccine development as both national success and global public good. Economic-Health Nexus messaging (30%) integrated pandemic response with global economic recovery narratives, acknowledging economic interdependence while emphasizing China’s role in global supply chain stability. This dual emphasis reflects sophisticated understanding of how domestic health policies intersect with global economic systems. International Isolation Phase (March 2021-November 2022): Adaptive Policy Convergence and Healthcare System Resilience resurged as zero-COVID policies faced mounting international criticism and economic pressure. This phase featured 53 press conferences, the highest absolute number, as authorities struggled to justify policy divergence from global approaches while managing increasing international isolation pressures. Communication during this phase revealed tensions between domestic policy commitments and international pressure for convergence. Healthcare System Resilience messaging (40%) emphasized system capacity and policy effectiveness to justify continued zero-COVID approaches despite international criticism. Adaptive Policy Convergence messaging (25%) introduced flexibility language (“scientific precision,” “dynamic adjustment”) that provided linguistic foundation for subsequent policy transitions while maintaining surface policy consistency. The emergence of “optimization” terminology during late 2022 represents sophisticated semantic governance, enabling policy flexibility without explicit acknowledgment of international pressure influence. This linguistic strategy demonstrates how authoritarian communication systems can prepare for policy transitions through gradual semantic adjustment rather than direct policy reversal announcements. Global Alignment Phase (December 2022-February 2023): Transnational Health Governance and Economic-Health Nexus gained prominence as China rapidly converged with international endemic management approaches. This phase encompassed 24 press conferences emphasizing policy “optimization” and alignment with global health governance recommendations. Communication strategy reframed policy changes as adaptive evolution rather than external capitulation, demonstrating sophisticated crisis termination under transnational pressure. Transnational Health Governance messaging (35%) emphasized China’s integration with global health governance frameworks and alignment with WHO recommendations for endemic management. Economic-Health Nexus messaging (40%) prioritized economic recovery and international integration, reflecting recognition that continued policy divergence threatened economic interdependence relationships essential for development objectives. Phase-Based Press Conference Title Keyword Evolution and Pandemic Policy Correlation (2020-2023) Pandemic Phase Press Conferences Total Keywords Unique Keywords Dominant Keywords (Top 6) Policy Context and Correlation Communication Strategy Indicators Table 5 (Continued) Pandemic Phase Press Conferences Total Keywords Unique Keywords Dominant Keywords (Top 6) Policy Context and Correlation Communication Strategy Indicators (Continued on next page) International Scrutiny Phase (Jan–Mar 2020) 36 347 179 Epidemic (疫情), Situation (情况), Prevention Control (防控), Guarantee (保障), Enterprise (企业), Work Resumption (复工) Wuhan lockdown implementation, national emergency response activation, initial economic support measures for enterprises, comprehensive crisis mobilization Crisis emergence communication: Highest vocabulary diversity, comprehensive response messaging, emphasis on situation control and enterprise support Global Cooperation Phase (Apr 2020–Feb 2021) 34 258 123 Epidemic (疫情), Prevention Control (防控), COVID-19 (新冠), Vaccine (疫苗), Pneumonia (肺炎), Medical (医疗) Vaccine development acceleration, mass vaccination campaign launch, gradual reopening preparations, expert consultation integration, normalization planning initiation Vaccine transition communication: Scientific achievement emphasis, vaccination infrastructure development, medical system strengthening, expert authority integration International Isolation Phase (Mar 2021–Nov 2022) 65 429 97 Epidemic (疫情), Prevention Control (防控), Vaccine (疫苗), Vaccination (接种), Scientific (科学), Precision (精准) Zero-COVID policy intensification, Shanghai lockdown implementation, scientific precision policy introduction, Delta and Omicron variant responses, strict enforcement measures Intensification communication: Highest frequency period, enforcement language dominance, scientific precision terminology adoption, policy justification focus Global Alignment Phase (Dec 2022–Feb 2023) 19 102 51 Key/Priority (重点), Epidemic (疫情), Prevention Control (防控), Population (人群), Medical (医疗), Guarantee (保障), Optimization (优化) Zero-COVID policy relaxation, optimization measures introduction, endemic transition management, vulnerable population focus, medical service enhancement, Spring Festival normalization Endemic adaptation communication: Targeted population focus, optimization terminology emergence, medical service emphasis, reduced epidemic emphasis Discussion Theoretical Contributions: Challenging Linear Crisis Models and Authoritarian Frame Dynamics This study makes two pivotal theoretical contributions that fundamentally reconceptualize crisis communication dynamics in extended emergencies. First, the empirical analysis reveals a cyclical frame reinforcement model that directly challenges and modifies the linear progression assumptions that have dominated crisis communication theory since Coombs’ foundational work. Traditional crisis lifecycle models conceptualize crisis communication as unidirectional temporal development—progressing sequentially from pre-crisis awareness through acute crisis response to post-crisis recovery—with the implicit assumption that communication strategies evolve forward without returning to previous phases . This linear paradigm treats crisis communication as a problem-solving sequence where each phase builds upon the previous one, ultimately culminating in resolution and organizational learning. The Chinese COVID-19 data fundamentally contradicts this linear assumption, revealing instead a recursive pattern where frames undergo strategic cyclical intensification and redeployment. The empirical evidence demonstrates that crisis communication in extended emergencies operates through what can be termed “spiral progression”—a dynamic where previously deployed frames are not abandoned but rather stored as strategic resources for future reactivation. This cyclical mechanism—where “retired” frames are strategically reactivated, modified, and redeployed for new circumstances—represents a fundamental theoretical advancement that requires crisis communication models to account for recursive rather than linear temporal dynamics. The theoretical implications extend beyond simple model modification to challenge core assumptions about crisis narrative development. Where traditional models assume progressive frame abandonment as crises evolve, the cyclical reinforcement model reveals that effective extended crisis communication operates through iterative adaptation cycles that treat previous frames as renewable strategic assets. This finding necessitates theoretical frameworks that model recursive intensification as a core feature of protracted crisis management, fundamentally altering how scholars conceptualize the relationship between time, narrative evolution, and communication effectiveness in extended emergencies. The cyclical frame reinforcement model proposed in this study foregrounds the deliberate, strategic redeployment of previously shelved frames rather than the involuntary re-entry into operational phases. It explains how communicators actively revive earlier discursive packages—often in altered form—to maintain legitimacy or mobilize compliance even when the material threat profile has changed. This distinction highlights the unique contribution of the present research: it shifts analytical focus from organizational process loops to rhetorical strategy cycles, revealing how narrative tools themselves become resources that can be stored, re-activated, and reconfigured across protracted emergencies. Second, the analysis identifies semantic governance as a distinctive mechanism of authoritarian crisis communication that extends framing theory into the domain of regime legitimacy maintenance. Unlike democratic contexts where policy reversals typically require explicit acknowledgment and justification due to pluralistic discourse environments, the Chinese case demonstrates how controlled information ecosystems enable sophisticated linguistic engineering to preserve governmental credibility during major policy transitions. The transition from “zero-COVID” to “coexistence” messaging exemplifies semantic governance in action: rather than acknowledging policy failure, authorities employed strategic euphemism (“optimization”), temporal reframing (“new phase”), and victory narratives (“decisive success”) to transform policy reversal into adaptive evolution. This linguistic management represents a form of soft power governance where semantic control becomes a mechanism for exercising authority over public perception, enabling regimes to navigate policy contradictions without appearing to falter. The theoretical significance lies in demonstrating how authoritarian communication systems can leverage discourse monopoly to achieve frame transformation impossible in competitive information environments. This insight expands framing theory beyond its traditional focus on competitive discourse dynamics (Chong and Druckman 2007) to encompass how controlled information systems generate unique opportunities for strategic narrative management that preserve legitimacy while enabling policy adaptation. The analysis reveals that "semantic governance" in authoritarian contexts transcends mere administrative control over information flows, constituting instead a systematic discursive capacity for meaning construction . Through the strategic establishment of acceptable semantic boundaries, the manipulation of keyword emotional orientations, and the systematic "addition, deletion, and substitution" of core vocabulary across different crisis phases, governmental actors achieve the reallocation of public emotions and attribution logic without substantially altering underlying policy objectives. This monopolization of symbolic resources enables regimes to rewrite potential policy failures—such as the termination of zero-COVID strategies—as strategic upgrades, thereby achieving what might be termed "continuity through policy discontinuity" . In contrast to democratic contexts that rely on public deliberation to modify narratives, semantic governance demonstrates an alternative pathway for legitimacy maintenance through discursive recoding rather than discursive competition . Semantic governance contributes two distinctive insights to crisis communication scholarship. First, the narrative resilience mechanism operates through gradual semantic adjustments—such as the progression from "zero-COVID" to "optimization" to "coexistence"—enabling authorities to absorb external shocks while preserving overarching narrative frameworks . This demonstrates superior narrative flexibility compared to simple media censorship, revealing sophisticated discursive elasticity that maintains interpretive coherence despite policy volatility . Second, semantic governance functions as a legitimacy transformation bridge , connecting performance-based legitimacy with performative legitimacy through the intermediary mechanism of "narrative legitimacy" . This enables regimes to maintain psychological dominance over public perception through semantic recoding when performance indicators falter, suggesting that traditional crisis lifecycle models require supplementation with a pervasive "semantic adaptation" component . Such theoretical expansion explains how authoritarian systems accomplish crisis narrative self-repair and reproduction through controlled discourse systems in the absence of institutionalized accountability mechanisms. Theoretical Positioning: Dialogue with International Crisis Communication Scholarship The empirical findings from this Chinese case study necessitate theoretical positioning within the broader field of crisis communication. By revealing cyclical frame reinforcement and semantic governance dynamics, this research dialogues with international crisis communication scholarship to both challenge and enrich existing models. Firstly, the evidence of recursive frame deployment invites a reconsideration of widely accepted crisis stages models beyond Chinese or authoritarian contexts. While cyclicality was observed in China’s crisis narrative, future research should examine whether elements of frame recycling appear in protracted crises elsewhere. Integrating our cyclical reinforcement model with models like ( coombs2021recycle? )’s recycle–recrisis could yield a more universal understanding of crisis communication patterns when crises are prolonged or recurring. Secondly, the concept of semantic governance underscores how political context can fundamentally alter crisis communication mechanisms. In democratic settings, crisis communication effectiveness is often tied to managing a contested information environment, as stakeholders publicly debate narratives (Chong and Druckman 2007). The Chinese case suggests that in controlled media environments, narrative flexibility can substitute for public debate. Scholars should explore to what extent semantic governance tactics—like euphemisms or strategic re-framings—are present or viable in hybrid regimes or even democracies under certain conditions (e.g., wartime censorship or emergency laws). Thirdly, by focusing on how global pressures mediate domestic communication (and vice versa), this study aligns with calls for a more internationalized crisis communication theory (Hajer, Wassila, and Moufida 2015). Our findings support the notion that crisis communication strategies must be analyzed within a multi-level governance context, acknowledging that global interdependence and transnational norms increasingly shape national narratives. This Chinese case thus contributes a concrete example of how global forces (WHO guidelines, international opinion, etc.) can be internalized and linguistically managed within state narratives. Finally, the research highlights an interplay between performance legitimacy and narrative legitimacy, resonating with frameworks from political science on authoritarian resilience (Holbig 2023). It suggests crisis communication scholars should incorporate insights from comparative politics, recognizing that the goals and methods of crisis framing may differ across regimes not only in degree but in kind. By engaging with interdisciplinary perspectives, the refined theoretical constructs proposed here—cyclical frame reinforcement and semantic governance—can be tested and elaborated in varied socio-political contexts, advancing a more globally attuned crisis communication scholarship. Conclusion This longitudinal frame analysis of Chinese government COVID-19 press conferences (2020-2023) has provided comprehensive insights into crisis communication dynamics during an extended global health emergency. Through computational topic modeling and qualitative interpretation, the study documented systematic frame evolution across four distinct pandemic phases, revealing sophisticated governmental communication strategies that adapted to changing epidemiological, economic, and social conditions. The study also points to how government public health messaging served a critical function in legitimizing stringent interventions, sustaining vaccine uptake, and gradually guiding citizens toward post-crisis normalcy. Communication strategies often integrated moral appeals, scientific justifications, and nationalistic or war-like metaphors to anchor public compliance and deter misinformation. This multi-frame approach underscores the complexity of large-scale, prolonged crisis communication, where no single narrative can continuously suffice. While this study provides comprehensive analysis of Chinese government COVID-19 crisis communication, several limitations merit acknowledgment alongside future research directions that can extend understanding of crisis framing dynamics. Methodologically, the LDA approach, while enabling systematic analysis of large textual corpora, may overlook nuanced rhetorical strategies, irony, or culturally-specific metaphors significant in Chinese political discourse. The exclusive focus on official press conferences, though justified by their authoritative status, excludes other communication channels such as local government messaging, social media posts, and policy documents that may reveal different framing strategies or internal tensions within governmental messaging. Future research should prioritize comparative analysis across multiple political systems and cultural contexts to validate and refine theoretical insights, enabling identification of universal versus system-specific patterns in crisis framing strategies. Reception-focused research represents a critical direction, requiring mixed-methods approaches combining computational analysis of social media responses, survey research across demographic segments, and ethnographic investigation of community frame interpretation. The authors acknowledge the support provided by the data collection platforms and the valuable insights contributed by the research participants. Special thanks to the reviewers for their constructive feedback that significantly improved this manuscript. Declarations Funding : This research has not got any funding. Conflict of interest/Competing interests : The authors declare no competing interests. Ethics approval and consent to participate : All data are drawn from publicly available government sources; no personal information is involved. The study complies with the PRC Regulations on Open Government Information and academic integrity standards. Consent for publication : Yes. Data availability : The dataset analyzed during the current study is available from the corresponding author on reasonable request. Materials availability : Not applicable. Code availability : The analysis code used in this study is available from the corresponding author on reasonable request. Author contribution : All authors contributed equally to the conception, design, analysis, and writing of this manuscript. References Benziman, Yuval. 2020. “‘Winning’ the ‘Battle’ and ‘Beating’ the COVID-19 ‘Enemy’: Leaders’ Use of War Frames to Define the Pandemic.” Peace and Conflict: Journal of Peace Psychology 26 (3): 247. Bernard, Natalie Reyes, Abdul Basit, Ernesta Sofija, Hai Phung, Jessica Lee, Shannon Rutherford, Bernadette Sebar, Neil Harris, Dung Phung, and Nicola Wiseman. 2021. “Analysis of Crisis Communication by the Prime Minister of Australia During the COVID-19 Pandemic.” International Journal of Disaster Risk Reduction 62: 102375. Blei, David M. 2012. “Probabilistic Topic Models.” Communications of the ACM 55 (4): 77–84. https://doi.org/10.1145/2133806.2133826 Blei, David M, Andrew Y Ng, and Michael I Jordan. 2003. “Latent Dirichlet Allocation.” Journal of Machine Learning Research 3 (Jan): 993–1022. Chan, Chi Kit, and Anthony Ying Him Fung. 2021. “From Soft Power to Sharp Power: China’s Media Image in Hong Kong’s Health Crises from 2003 to 2020.” Global Media and China 6 (1): 62–76. Chapman, Connor M, and DeMond Shondell Miller. 2020. “From Metaphor to Militarized Response: The Social Implications of ‘We Are at War with COVID-19’–Crisis, Disasters, and Pandemics yet to Come.” International Journal of Sociology and Social Policy 40 (9/10): 1107–24. Chen, Qiang, Chen Min, Wei Zhang, Ge Wang, Xiaoyue Ma, and Richard Evans. 2020. “Unpacking the Black Box: How to Promote Citizen Engagement Through Government Social Media During the COVID-19 Crisis.” Computers in Human Behavior 110: 106380. Chong, Dennis, and James N Druckman. 2007. “Framing Theory.” Annu. Rev. Polit. Sci. 10 (1): 103–26. Coombs, W Timothy, and Sherry Jean Holladay. 2014. “How Publics React to Crisis Communication Efforts: Comparing Crisis Response Reactions Across Sub-Arenas.” Journal of Communication Management 18 (1): 40–57. Dada, Sara, Heather Battles, Caitlin Pilbeam, Bhagteshwar Singh, Tom Solomon, and Nina Gobat. 2021. “Learning from the Past and Present: Social Science Implications for COVID-19 Immunity-Based Documentation.” Humanities and Social Sciences Communications 8 (1). Dau, Duc, and Katie Ellis. 2023. “From Bondi to Fairfield: NSW COVID-19 Press Conferences, Health Messaging, and Social Inequality.” Media International Australia 188 (1): 34–51. Entman, Robert M. 1993. “Framing: Toward Clarification of a Fractured Paradigm.” Journal of Communication 43 (4): 51–58. Goffman, Erving. 1974. Frame Analysis: An Essay on the Organization of Experience. Harvard University Press. Gui, Lili. 2021. “Media Framing of Fighting COVID-19 in China.” Sociology of Health & Illness 43 (4): 966–70. Hajer, Degachi, Chagra Wassila, and Ksouri Moufida. 2015. “Global Optimization Method for Min-Max MPC Based on Wiener and Hammerstein Model.” In 2015 7th International Conference on Modelling, Identification and Control (ICMIC) , 1–6. IEEE. Harper, Craig A, Liam P Satchell, Dean Fido, and Robert D Latzman. 2021. “Functional Fear Predicts Public Health Compliance in the COVID-19 Pandemic.” International Journal of Mental Health and Addiction 19 (5): 1875–88. He, Alex Jingwei, Yuda Shi, and Hongdou Liu. 2020. “Crisis Governance, Chinese Style: Distinctive Features of China’s Response to the Covid-19 Pandemic.” Policy Design and Practice 3 (3): 242–58. Holbig, Heike. 2023. “China’s Response to the COVID-19 Pandemic: Navigating Internal and External Challenges.” In Democracy, State Capacity and the Governance of COVID-19 in Asia-Oceania , 244–66. Routledge. Huang, Chaolin, Yeming Wang, Xingwang Li, Lili Ren, Jianping Zhao, Yi Hu, Li Zhang, et al. 2020. “Clinical Features of Patients Infected with 2019 Novel Coronavirus in Wuhan, China.” The Lancet 395 (10223): 497–506. Jacobs, Thomas, and Robin Tschötschel. 2019. “Topic Models Meet Discourse Analysis: A Quantitative Tool for a Qualitative Approach.” International Journal of Social Research Methodology 22 (5): 469–85. Jacobsen, Kathryn H, A Alonso Aguirre, Charles L Bailey, Ancha V Baranova, Andrew T Crooks, Arie Croitoru, Paul L Delamater, et al. 2016. “Lessons from the Ebola Outbreak: Action Items for Emerging Infectious Disease Preparedness and Response.” EcoHealth 13: 200–212. Kickbusch, Ilona, Graham Lister, Michaela Told, and Nick Drager. 2013. Global Health Diplomacy: Concepts, Issues, Actors, Instruments, Fora and Cases . Springer. Kim, Do Kyun David, and Gary L Kreps. 2020. “An Analysis of Government Communication in the United States During the COVID-19 Pandemic: Recommendations for Effective Government Health Risk Communication.” World Medical & Health Policy 12 (4): 398–412. Kneuer, Marianne, and Stefan Wallaschek. 2023. “Framing COVID-19: Public Leadership and Crisis Communication by Chancellor Angela Merkel During the Pandemic in 2020.” German Politics 32 (4): 686–709. Labonté, Ronald, Katia Mohindra, and Ted Schrecker. 2011. “The Growing Impact of Globalization for Health and Public Health Practice.” Annual Review of Public Health 32 (1): 263–83. Lyu, Lin, Lily Suriani Binti Mohd Arif, and Ruzanna Binti Shahrin. 2024. “Analysis of Pandemic Reporting Framework of Mainstream New Media Based on the Reports of Typical Mainstream Media Wechat Official Account.” Studies in Media and Communication 12 (1): 79–89. MacKay, Melissa, Taylor Colangeli, Abhinand Thaivalappil, Ariana Del Bianco, Jennifer McWhirter, and Andrew Papadopoulos. 2022. “A Review and Analysis of the Literature on Public Health Emergency Communication Practices.” Journal of Community Health , 1–13. Maier, Daniel, Annie Waldherr, Peter Miltner, Gregor Wiedemann, Andreas Niekler, Alexa Keinert, Barbara Pfetsch, et al. 2021. “Applying LDA Topic Modeling in Communication Research: Toward a Valid and Reliable Methodology.” In Computational Methods for Communication Science , 13–38. Routledge. Moon, Suerie, John-Arne Røttingen, and Julio Frenk. 2017. “Global Public Goods for Health: Weaknesses and Opportunities in the Global Health System.” Health Economics, Policy and Law 12 (2): 195–205. Ning, Peishan, Peixia Cheng, Jie Li, Ming Zheng, David C Schwebel, Yang Yang, Peng Lu, Li Mengdi, Zhuo Zhang, and Guoqing Hu. 2021. “COVID-19–Related Rumor Content, Transmission, and Clarification Strategies in China: Descriptive Study.” Journal of Medical Internet Research 23 (12): e27339. Seeger, Matthew W. 2006. “Best Practices in Crisis Communication: An Expert Panel Process.” Journal of Applied Communication Research 34 (3): 232–44. Watkins, Daryl V, and Aaron D Clevenger. 2021. “US Political Leadership and Crisis Communication During COVID-19.” Cogent Social Sciences 7 (1): 1901365. Xie, Qihui, Yanan Xue, and Zhuojun Zhao. 2022. “Understanding the Scientific Topics in the Chinese Government’s Communication about COVID-19: An LDA Approach.” Sustainability 14 (15): 9614. Zhou, Cheng, Haoxin Xiu, Yuqiu Wang, and Xinyao Yu. 2021. “Characterizing the Dissemination of Misinformation on Social Media in Health Emergencies: An Empirical Study Based on COVID-19.” Information Processing & Management 58 (4): 102554. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7117519","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":494430934,"identity":"214afb16-270f-4568-ae71-b310fc173606","order_by":0,"name":"Liu Dandan","email":"","orcid":"","institution":"University of Malaya, Wilayah Persekutuan Kuala Lumpur","correspondingAuthor":false,"prefix":"","firstName":"Liu","middleName":"","lastName":"Dandan","suffix":""},{"id":494430935,"identity":"aec1a17f-e9b2-44c8-b99d-82d440186120","order_by":1,"name":"Siti Ezaleila Binti Mustafa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA00lEQVRIiWNgGAWjYHACxgMMBhYM/GA2G5F6gFokGCQbSNPCIMFgcIBYLfz8hx8c+FAgIW98IzuB4UPZYQbdGQn4tUg2HDM4OMNAwnDbjdwNjDPOHWYwu0FAi8HBBoPDPAYSjCAtzLxtRGixP8z+4fAfAwn7zTOAWv4So8WAjcfgMDDEEjdIALUwEqNF4gxPwcEeA4nkGWfebjjYcy6dx+zMA/xa+PuPb3zw44+NbX97LpBRZi1ndpyALSjgABDzMAiQogVq8QGStYyCUTAKRsHwBgD00kkK9WnZEQAAAABJRU5ErkJggg==","orcid":"","institution":"University of Malaya, Wilayah Persekutuan Kuala Lumpur","correspondingAuthor":true,"prefix":"","firstName":"Siti","middleName":"Ezaleila Binti","lastName":"Mustafa","suffix":""},{"id":494430936,"identity":"40e30e63-b5eb-4764-91bd-043f032c096b","order_by":2,"name":"NOR ZALIZA BINTI SARMITI","email":"","orcid":"","institution":"University of Malaya, Wilayah Persekutuan Kuala Lumpur","correspondingAuthor":false,"prefix":"","firstName":"NOR","middleName":"ZALIZA BINTI","lastName":"SARMITI","suffix":""}],"badges":[],"createdAt":"2025-07-14 06:23:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7117519/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7117519/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12992-025-01155-y","type":"published","date":"2025-11-04T00:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":88222333,"identity":"8c7fd2cc-7bc7-4ee0-8507-e216733943ae","added_by":"auto","created_at":"2025-08-04 08:06:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":96312,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7117519/v1/60d2b1f2713c100ea1202554.png"},{"id":95303333,"identity":"22622d81-4856-44bf-a505-71b0189a2278","added_by":"auto","created_at":"2025-11-06 13:55:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1569526,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7117519/v1/707403c1-876d-4d08-a977-38aa06dc38aa.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"From Zero-COVID to Global Alignment: Transnational Pressures and China’s Pandemic Communication Transformation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe COVID-19 pandemic radically reshaped global communication dynamics, compelling governments to deliver, requiring governments to provide frequent updates on infection rates, public health protocols, and evolving scientific knowledge (Seeger 2006). As the crisis unfolded in real time, one of the most visible and routine channels for official announcements became the government press conference. From the early stages of the outbreak in Wuhan, China, to similar practices in other nations, press conferences rapidly assumed a pivotal role in distributing accurate information on the epidemiological situation, clarifying preventive measures, and addressing public concerns regarding disruptions to daily life and economic stability (Kim and Kreps 2020; Kneuer and Wallaschek 2023). By providing a centralized platform for government spokespersons, health authorities, and occasionally scientific experts, these events aimed to instill confidence, coordinate policy responses, and guide public behaviors in an atmosphere rife with uncertainty. A central advantage of official or government press conferences is the projection of unified, authoritative messaging (MacKay et al. 2022). In high-stakes crises such as COVID-19, citizens expect clear guidelines about mask usage, social distancing, testing, and eventual vaccination. Press conferences permit government officials to present this guidance as a coherent narrative, reducing discrepancies that might otherwise arise if multiple agencies or ministries were to communicate independently. This consolidated approach can lessen confusion, maintain institutional legitimacy, and ensure that policy changes \u0026nbsp;—such as new travel restrictions or amendments to quarantine durations— \u0026nbsp; are presented as part of an organized governmental strategy (Seeger 2006). In China, for instance, regular briefings by the Joint Prevention and Control Mechanism at the State Council sought to demonstrate unwavering focus and swift decision-making in the face of fluctuating daily case counts and variant threats (He, Shi, and Liu 2020). Moreover, press conferences allow a formal mechanism for media representatives to question officials and obtain clarifications, albeit within certain procedural constraints (Dau and Ellis 2023). This interplay, even if sometimes constrained, can foster a veneer of transparency: when officials publicly address challenges, it indicates accountability to the populace. Insofar as reporters are permitted to probe policy rationales, these interactions can reveal strategic priorities, from procurement of medical supplies to economic stimulus for pandemic-hit industries. As a result, press conferences function as communicative \"gateways\" through which the public can glean at least a portion of the rationale behind policy moves (Chan and Fung 2021).\u003c/p\u003e\n\u003ch2\u003eFraming and Its Impact on Public Understanding\u003c/h2\u003e\n\u003cp\u003eFraming, fundamentally, is the process of selecting certain aspects of reality and making them more salient in a communication text, in order to define problems, diagnose causes, make moral judgments, or propose remedies (Entman 1993). In the context of a global health emergency, where the stakes include public compliance and individual safety, how government spokespersons frame” a topic can significantly influence how citizens interpret both the severity of the crisis and the viability of proposed solutions (Chong and Druckman 2007). For instance, by framing COVID-19 as a war” (Benziman 2020), leaders can invoke urgency and unity, shaping the public’s willingness to accept stringent measures. Conversely, a frame that overly normalizes the situation may prompt complacency or insufficient adherence to guidelines (Harper et al. 2021). Press conferences are particularly potent sites for framing because they often represent the first authoritative source of information on policy shifts or critical health data (Seeger 2006). The rhetorical choices employed—whether acknowledging uncertainties, highlighting successes, or calling for civic duty—can reinforce specific narratives that trickle down into mainstream media reporting and user-generated content on social media (Zhou et al. 2021). In effect, these official statements set the initial interpretive framework or \"top-down frames\" for broader public discourse. Journalists rely on quotes and figures from these briefings, which can then be adapted or critiqued in editorials and news coverage, while social media users may echo or dispute the official terminology, adding emotional or personal perspectives (Chen et al. 2020). Thus, the frames introduced in press conferences play a foundational role in shaping subsequent information flows across multiple communication channels.\u003c/p\u003e\n\u003ch2\u003eAim and Research Questions\u003c/h2\u003e\n\u003cp\u003eBuilding on the observations above, this study sets out to analyze how the Chinese government, through its official press conferences, established and maintained specific frames during the COVID-19 pandemic. The objective is to examine government framing strategies in official COVID-19 press conferences and their evolution over time. The study raises three core research questions:\u003c/p\u003e\n\u003cp\u003eRQ1: What predominant frames characterize Chinese government COVID-19 press conferences, especially in relation to epidemic control, vaccination, economic recovery, and other salient themes?\u003c/p\u003e\n\u003cp\u003eRQ2: In what ways did these Chinese governmental communication frames evolve over different phases of the pandemic—from the initial outbreak to peak crisis management and eventual easing of restrictions—and what factors prompted these shifts?\u003c/p\u003e\n\u003cp\u003eRQ3: What role did the Chinese government’s public health messaging play in managing the COVID-19 pandemic, including fostering compliance, reassuring citizens, and addressing misinformation or emotional anxieties?\u003c/p\u003e\n\u003cp\u003eBy systematically analyzing the press conference transcripts, this study aims to advance crisis communication theory by examining both the temporal dynamics of frame evolution and the mechanisms of authoritarian crisis discourse. This macro-level perspective is essential because it sets the baseline framework that official media outlets subsequently refine in their coverage, and that citizens on social media endorse or contestfor media coverage and public discourse (Lyu, Arif, and Shahrin 2024). Moreover, adopting a longitudinal approach—tracking frames from early 2020 through early 2023—allows for insight intoshows how crisis communication adapts to changing epidemiological and sociopolitical conditions. It acknowledges that what a government emphasizes at the outbreak stage may differ substantially from what it underscores amid vaccination rollouts or when loosening restrictions for social and economic normalcy. Focusing on government press conferences also taps into prior research in crisis communication studies that underscores the performative element of official addresses (Seeger 2006). Press conferences serve not only to transmit facts but also to display governmental competence, reassure the public, and maintain national unity (Chan and Fung 2021). Hence, understanding the interplay of factual announcements, emotional appeals, and strategic justifications within these briefings gives researchers a window intoprovides insight into how leadership navigates and constructs crisis narratives. (Entman 1993; Goffman 1974) alongside topic modeling (Maier et al. 2021) to generate both a quantitative mapping of emergent themes and a qualitative interpretation of how these themes function as frames.to produce a quantitative mapping of themes and a qualitative interpretation of frames\u003c/p\u003e"},{"header":"Literature Review","content":"\u003cp\u003eThis section provides an expanded and more analytical discussion of framing theory in government communication, empirical research on government discourse during health crises, and the relevance of topic modeling techniques. In response to prior critiques, the text below integrates a comparative perspective on authoritarian versus democratic systems, incorporates the crisis communication phases proposed by (Coombs and Holladay 2014), and explores framing subcategories—such as episodic vs. thematic, and gain vs. loss frames—to assess their potential impact on public trust and compliance.\u003c/p\u003e\n\u003ch2\u003eFraming Theory and Government Communication\u003c/h2\u003e\n\u003cp\u003eFraming theory underscores how communicative actors—government leaders, spokespersons, and agencies—select and emphasize certain aspects of an issue to shape public perception and guide responses (Entman 1993; Chong and Druckman 2007). At its core, framing is about organizing meaning, highlighting particular narratives or dimensions of a phenomenon while omitting others, thus steering how the audience interprets events and what solutions they see as appropriate. organizes meaning by emphasizing certain aspects and omitting others, steering how audiences interpret events and identify solutions (Goffman 1974). In crisis contexts like pandemics, the urgency and high stakes of public health measures mean that framing becomes a pivotal tool for governments to generate trust, cooperation, and rapid behavior change (Seeger 2006). However, governments do not all frame crises in the same way, as political systems significantly influence both the style and content of official messages. In authoritarian regimes, where information flows are more centrally controlled, top-down directives and nationalistic frames can dominate. Government communications might emphasize collective duty and heroic narratives of frontline workers, invoking unity and portraying any dissent as undermining societal well-being (Benziman 2020). Conversely, democratic governments often contend with pluralistic media environments and must negotiate policy framing with diverse stakeholders. While they, too, may use moral imperatives and metaphors—such as the “war on COVID-19”—the presence of an active free press and opposition parties can foster competing frames that highlight potential policy failures or trade-offs. While democratic governments may also use “war” metaphors, an active free press and opposition parties foster competing frames highlighting policy failures or trade-offs (Chong and Druckman 2007).. Building on frame evolution theory, governments adjust their framing as a crisis progresses through different stages. (Coombs and Holladay 2014) delineates crisis communication phases: pre-crisis, acute crisis, and post-crisis. In pandemics, the pre-crisis phase often involves warnings or minimal communications designed to alert the public without causing alarm. The acute phase features intensified messaging focusing on urgent measures—social distancing, lockdowns, or vaccination. The post-crisis phase typically shifts attention to recovery, rebuilding trust, and mitigating long-term impacts. Within each phase, frames may evolve, moving from a “war metaphor” emphasizing threat and urgency to more thematic frames centering on societal recovery or collective resilience. Framing subcategories also merit attention due to their influence on public trust and compliance. For example, episodic framing personalizes the crisis through individual stories, aiming to elicit empathy or fear, while thematic framing places the crisis in broader structural or policy contexts (Chong and Druckman 2007). Governments can also employ gain vs. loss frames to highlight either the benefits of compliance (e.g., protecting vulnerable populations) or the dire consequences of non-compliance (e.g., increased mortality rates). Research in health communication suggests that gain-framed messages can enhance public compliance by emphasizing positive outcomes, whereas loss-framed messages may provoke fear but risk alienating certain segments of the audience (Dada et al. 2021). Balancing these sub-framing strategies is crucial to maintaining both credibility and public cooperation. In sum, framing theory provides a conceptual lens for evaluating how governments in different political contexts structure their crisis narratives. Whether through war metaphors, duty-based appeals, or economic recovery frames, these communicative choices shape how citizens perceive their responsibilities and how they respond in real time perceive their responsibilities and respond. In pandemics, effective framing not only informs the public but also motivates collective action—whether by fostering trust in authoritarian settings with centralized messaging or by navigating complex media ecosystems in democratic environments.\u003c/p\u003e\n\u003ch2\u003eEmpirical Research on Government Discourse in Crises\u003c/h2\u003e\n\u003cp\u003eEmpirical studies of government framing in public health emergencies—SARS, Ebola, Zika, and COVID-19—reveal that political system type, cultural context, and the crisis stage significantly affect official messaging (Kim and Kreps 2020). In authoritarian contexts, messages tend to highlight the protective role of the state and the importance of public obedience, often combined with thematic frames of collective struggle (Huang et al. 2020). During the 2003 SARS outbreak, for instance, Chinese government communications evolved from limited, guarded reports to more proactive disclosures under international scrutiny, illustrating a strategic adaptation in framing (Gui 2021; Ning et al. 2021). Meanwhile, Western democracies addressing the same crisis had to balance transparency against potential overreaction, with leaders often facing critical media queries that complicated a singular, unified frame. The Ebola crisis in West Africa further demonstrates how local beliefs and cultural practices influence government frames. Official discourse in Liberia and Sierra Leone centered on moral appeals for compliance with quarantine measures, invoking communal duty and respect for the deceased (Jacobsen et al. 2016). In Western countries—less directly affected—the frame shifted toward preventing imported cases, emphasizing border control and biomedical interventions. These divergent emphases underscore how episodic story-based appeals (e.g., accounts of individual Ebola victims) coexisted with thematic messages (e.g., societal or international cooperation), and how local authorities navigated tension between public health directives and deeply held cultural rituals (Dada et al. 2021). With COVID-19, research has documented further variations in government discourse across political systems. Authoritarian leaders often leveraged “war metaphors” early in the pandemic, using centralized daily briefings to communicate strict lockdown policies and mobilize national solidarity (Benziman 2020). Democratic leaders also invoked war-like rhetoric, but faced more scrutiny from media outlets, opposition parties, and health experts; in these settings, alternative frames—focusing on economic relief, social welfare, or the moral imperative to protect vulnerable populations—emerged alongside official statementsbut faced greater scrutiny, and alternative frames (economic relief, social welfare, protecting vulnerable populations) emerged alongside official narratives (Kneuer and Wallaschek 2023).. As the pandemic wore on, many governments shifted from acute-crisis framing (lockdowns, strict measures) to recovery-oriented frames emphasizing resumption of economic and social activitiesa return to normalcy (Bernard et al. 2021). These phased transitions align with (Coombs and Holladay 2014)’s crisis communication lifecycle, as governments refined their narratives to maintain public compliance while restoring normalcyrestoring stability. Despite considerable case studies, systematic analyses of official press conference transcripts remain relatively scarce. Scholars have often relied on policy documents or media reports, potentially overlooking the real-time rhetorical strategies officials use. Yet press conferences are pivotal events where governments disclose new data, address rumors, and reinforce compliance norms (Chapman and Miller 2020).\u003c/p\u003e\n\u003ch2\u003eRelevance of LDA and Topic Modeling\u003c/h2\u003e\n\u003cp\u003eGiven the extensive volume of text generated in government press conferences—especially over a multi-year pandemic—researchers increasingly employ computational techniques like Latent Dirichlet Allocation (LDA) to identify and track recurring themes. LDA is a probabilistic model that infers hidden patterns from word co-occurrence, dividing a corpus into thematically cohesive “topics” (Blei, Ng, and Jordan 2003; Maier et al. 2021). This approach offers three major advantages in analyzing pandemic-related government discourse: First, press conferences can produce millions of words, making purely manual coding impractical (Xie, Xue, and Zhao 2022). LDA automates the initial categorization of content, highlighting prominent themes—such as lockdown measures, vaccination campaigns, or economic relief. Second, LDA’s data-driven grouping can reveal unexpected patterns or sub-themes that might be missed if researchers impose predefined coding categories (Jacobs and Tschötschel 2019). It thus serves as a check against researcher bias, ensuring that the data itself guides the identification of salient topics. Third, LDA can be applied to different crisis phases (Coombs and Holladay 2014), detecting how topics emerge, evolve, or vanish over time (Blei 2012). This is critical in comparing responses between authoritarian and democratic settings, or in noting how frames shift from “immediate threat” to “recovery” emphasis. However, LDA alone cannot fully capture the nuances of framing. Topics identified by the model may cluster around high-frequency terms like “mask,” “vaccine,” or “economic relief,” but may overlook subtler discursive devices such as metaphors, moral imperatives, or the interplay between episodic and thematic framing. For instance, “war metaphors” may not coalesce around a single keyword; instead, they arise from repeated references to “fight,” “victory,” “battle,” and “frontline heroes” (Benziman 2020). Detecting gain vs. loss frames similarly requires close attention to how governments articulate outcomes (e.g., “preventing deaths” vs. “facing escalating fatalities”). Consequently, mixed-method approaches are recommended (Chong and Druckman 2007; Xie, Xue, and Zhao 2022). After LDA identifies the main topics, researchers can conduct qualitative frame analysis of specific segments, examining rhetorical elements—such as moral appeals, emotional tone, or policy justifications—to interpret how framing shapes public trust and compliance (Watkins and Clevenger 2021). This dual strategy ensures that researchers capture both macro-level patterns and the micro-level discursive strategies that underpin those patterns. For the present study, focusing on Chinese government press conferences, LDA can reveal the shifting emphases—ranging from disease containment to economic revival—across various COVID-19 phases. A subsequent manual or semi-automatic review can then map these topic clusters onto recognized frames—like “war metaphors,” “solidarity appeals,” or “economic recovery.” By incorporating episodic vs. thematic and gain vs. loss framing dimensions, the analysis can further elucidate how a centralized, authoritarian communication apparatus evolves its narrative over time to maintain legitimacy, manage public sentiment, and encourage compliance. This combined approach aligns with foundational insights from framing theory (Entman 1993; Goffman 1974) and accounts for the contextual and dynamic nature of crisis communication (Coombs and Holladay 2014). Ultimately, it offers a more comprehensive view of how government discourse shapes, and is shaped by, public perceptions throughout a protracted global health emergency.\u003c/p\u003e"},{"header":"Methodology","content":"\u003ch2\u003eResearch Design and Theoretical Framework\u003c/h2\u003e\n\u003cp\u003eThis study employs a longitudinal, mixed-methods approach to analyze how transnational pressures influenced China’s pandemic communication transformation from zero-COVID policies to global alignment strategies between February 2020 and February 2023. The research design integrates computational text analysis with qualitative framing theory to examine how globalization processes shaped public health communication strategies during an unprecedented global health crisis (Labonté, Mohindra, and Schrecker 2011). The theoretical framework draws upon globalization and health scholarship that emphasizes how transnational dynamics influence domestic health policy communication, particularly in contexts where national health systems must navigate between domestic priorities and international pressures (Kickbusch et al. 2013). The methodological approach recognizes that pandemic communication represents a critical intersection between global health governance and national crisis management, where communication strategies reflect broader tensions between sovereignty and interdependence in global health systems (Moon, Røttingen, and Frenk 2017). Press conferences serve as particularly valuable sites for analyzing these dynamics because they function as primary channels through which governments articulate their positioning within global health governance frameworks while addressing domestic constituencies. The longitudinal design enables examination of how communication strategies evolved in response to changing international contexts, including World Health Organization policy shifts, international travel restrictions, vaccine diplomacy initiatives, and global economic pressures. The research adopts a phase-based analytical framework that aligns with established crisis communication models while incorporating insights from globalization and health literature regarding policy adaptation under transnational pressure (Coombs and Holladay 2014; Labonté, Mohindra, and Schrecker 2011). This approach acknowledges that crisis communication in globalized contexts involves continuous negotiation between domestic imperatives and international expectations, with communication strategies serving as mechanisms for managing these competing pressures. The temporal segmentation enables detailed analysis of how specific transnational factors—including international criticism, economic interdependence, and global health governance expectations—influenced communication frame evolution across different pandemic phases. This study adopts a longitudinal mixed-methods design (combining topic modeling and framing analysis) to examine how transnational pressures shaped China’s pandemic press conference communication from the initial outbreak through the policy alignment in 2023. It integrates computational text analysis with framing theory, situating pandemic communication at the nexus of global health governance and domestic crisis management. The approach aligns with crisis phase models (Coombs and Holladay 2014) and draws on globalization scholarship (Labonté, Mohindra, and Schrecker 2011), allowing us to track how international criticism, economic interdependence, and global health governance expectations influenced the evolution of official frames over time.\u003c/p\u003e\n\u003ch2\u003eData Collection and Corpus Construction\u003c/h2\u003e\n\u003cp\u003eThe study corpus comprises 154 official press conference transcripts from China’s State Council Joint Prevention and Control Mechanism, representing the complete record of central government COVID-19 communication throughout the study period. These transcripts were systematically collected from the official Chinese government website (Gov.cn) using automated extraction protocols that ensured comprehensive coverage while maintaining data integrityusing automated extraction to ensure comprehensive coverage. The selection of central government communications reflects the study’s focus on how national-level authorities navigate transnational pressures in global health contexts, as opposed to local implementation dynamics focuses on national-level communications to capture transnational influence, rather than local-level messaging. The corpus construction strategy prioritized institutional consistency and policy authority by focusing exclusively on the State Council Joint Prevention and Control Mechanism, which served as China’s primary coordination body for pandemic response and international engagement. This institutional focus ensures analytical coherence while capturing communications most directly influenced by transnational pressures, including international criticism of early pandemic response, global vaccine distribution negotiations, and international economic recovery coordination. The resulting dataset comprises approximately 16.9 million Chinese characters, equivalent to 2.9 million word tokens following segmentation, providing substantial textual depth for computational analysis. Temporal coverage spans from February 2020 through February 2023, encompassing the complete cycle of China’s pandemic response from initial outbreak management through policy normalization. This timeframe captures critical periods of international engagement and policy adjustment, including early international criticism and transparency pressures, global vaccine development competition, international travel restriction negotiations, and eventual alignment with global endemic management approaches. The comprehensive temporal scope enables analysis of how sustained transnational pressures influenced long-term communication strategy evolution rather than merely short-term tactical adjustments. Data collection protocols incorporated quality assurance measures to ensure textual accuracy and completeness. Automated extraction targeted official statements, expert responses, and journalist questions while excluding non-textual elements that might introduce analytical noise. The extraction process maintained respectful crawling frequencies in accordance with website usage policies while ensuring comprehensive coverage of all available transcripts. Post-collection verification procedures confirmed that the corpus represents a complete census of central government COVID-19 communications during the study period, providing maximum representativeness for analyzing official discourse evolution.\u003c/p\u003e\n\u003ch2\u003eTemporal Segmentation and Phase Definition\u003c/h2\u003e\n\u003cp\u003eThe corpus was segmented into four distinct phases based on major policy milestones and international developments that reflected changing transnational pressures and global health governance dynamics. This segmentation strategy enables comparative analysis of how communication frames evolved in response to specific international contexts and transnational influences throughout the pandemic timeline. The International Scrutiny Phase (January-March 2020) encompasses the period of intense international attention and criticism regarding China’s initial pandemic response, including World Health Organization investigations, international media scrutiny, and diplomatic tensions over transparency and information sharing. This phase captures communication strategies developed under unprecedented international pressure for accountability and transparency in global health emergency contexts. Government discourse during this period reflected attempts to balance domestic crisis management with international reputation management and diplomatic relationship preservation. The Global Cooperation Phase (April 2020-February 2021) marks the transition toward international collaboration and competitive positioning in global vaccine development and distribution networks. This phase encompasses China’s engagement with global vaccine diplomacy initiatives, participation in international research collaboration, and positioning within global health governance frameworks. Communication strategies during this period reflect attempts to demonstrate international leadership while maintaining domestic policy autonomy, particularly regarding vaccine development sovereignty and distribution priorities. The International Isolation Phase (March 2021-November 2022) coincides with growing international criticism of zero-COVID policies and increasing economic and diplomatic pressures for policy alignment with global approaches. This phase captures communication strategies developed in response to international travel restrictions, economic isolation pressures, and diplomatic tensions over pandemic policy divergence. Government discourse increasingly emphasized policy justification and sovereignty protection while managing growing international pressure for policy convergence. The Global Alignment Phase (December 2022-February 2023) represents the period of rapid policy convergence with international approaches following sustained transnational pressure and economic imperatives. This phase encompasses the dramatic policy reversal toward endemic management approaches that aligned with global health governance recommendations and international economic integration requirements. Communication strategies during this period reflect efforts to frame policy changes as adaptive evolution rather than external capitulation while maintaining regime legitimacy throughout the transition.\u003c/p\u003e\n\u003ch2\u003eComputational Text Analysis and Topic Modeling\u003c/h2\u003e\n\u003cp\u003eThe study employs Latent Dirichlet Allocation (LDA) topic modeling to systematically identify and track thematic patterns across the extensive corpus, enabling analysis of how transnational pressures influenced communication frame evolution over time (Blei, Ng, and Jordan 2003). This computational approach provides objective identification of recurring themes while enabling temporal analysis of frame prominence and evolution across different phases of international engagement. The methodology integrates computational rigor with qualitative interpretation to capture both broad patterns and nuanced shifts in communication strategies. Text preprocessing procedures incorporated Chinese language-specific considerations, including segmentation using Jieba tokenization, removal of function words and boilerplate language, and consolidation of synonymous terms to minimize semantic fragmentation. The preprocessing pipeline maintained semantic integrity while optimizing the corpus for computational analysis, ensuring that identified topics reflect genuine thematic patterns rather than linguistic artifacts. Quality control measures included manual review of preprocessing outcomes and iterative refinement to optimize topic coherence and interpretability. Model specification involved systematic optimization of hyperparameters through iterative testing of topic numbers (K) ranging from 5 to 25, with selection based on coherence metrics and qualitative interpretability assessments. The final model specification (K=8) balanced computational coherence with theoretical meaningfulness, ensuring that identified topics align with (coherence score: 0.56) broader crisis communication themes.\u003c/p\u003e\n\u003ch2\u003eFrame Analysis and Theoretical Integration\u003c/h2\u003e\n\u003cp\u003eThe study integrates computational topic identification with established framing theory to analyze how transnational pressures influenced communication strategy evolution throughout the pandemic. Frame analysis follows Entman’s conceptual framework, examining how topics function to define problems, diagnose causes, make moral evaluations, and suggest remedies within the context of global health governance and transnational pressure management (Entman 1993). This integration enables analysis of both manifest content patterns and latent strategic functions of communication frames. Topic-to-frame mapping procedures involved systematic evaluation of computational topics against established crisis communication frame categories, with particular attention to how frames reflect transnational influence and global health governance positioning. Two independent researchers conducted preliminary mappings based on topic vocabulary and theoretical alignment, achieving 75% initial consensus with structured discussion resolving remaining disagreements. External validation by three additional experts yielded 83.3% agreement with final mappings, providing confidence in interpretive validity. The analytical framework incorporates insights from globalization and health scholarship regarding how transnational pressures influence domestic health policy communication, particularly focusing on sovereignty-interdependence tensions and legitimacy management strategies (Kickbusch et al. 2013; Labonté, Mohindra, and Schrecker 2011). Frame analysis examines how communication strategies navigate between domestic audience expectations and international pressure management, with particular attention to how frames evolve in response to changing transnational contexts and global health governance dynamics. Temporal frame analysis tracks how specific frames emerge, evolve, and decline across different phases of international engagement, enabling identification of communication adaptation patterns in response to transnational pressures. The methodology examines both frame content evolution and strategic function shifts, analyzing how similar thematic content serves different strategic purposes across different international contexts. This approach enables nuanced understanding of how globalization processes influence crisis communication strategies in complex political and health system contexts. The validation framework ensures methodological rigor through multiple verification procedures. Internal validation employs coherence metrics and stability testing to confirm computational reliability, while external validation compares results against independent data sources including policy documents and press conference titles. Expert consensus procedures provide additional verification of interpretive validity, ensuring that frame mappings reflect genuine theoretical alignment rather than analytical artifacts. This multi-layered validation approach strengthens confidence in findings while maintaining transparency regarding methodological limitations and assumptions.\u003c/p\u003e\n\u003ch2\u003eEthical Considerations and Data Availability\u003c/h2\u003e\n\u003cp\u003eAll data analyzed in this study consists of publicly available government communications, eliminating privacy concerns and ensuring compliance with research ethics standards. The press conference transcripts represent official government statements intended for public dissemination, with no personal or sensitive information requiring protection. The study methodology focuses exclusively on publicly available textual content, with no human subjects involvement or private data collection. Data collection procedures adhered to website usage policies and maintained respectful crawling frequencies to avoid disrupting official government websites. The automated extraction protocols incorporated appropriate delays and access limitations to ensure responsible data collection practices. All extracted content remains publicly accessible through official government channels, with the study corpus serving as a systematic compilation rather than creating new data accessibility issues. The complete dataset and analytical code are available for replication and verification purposes, supporting transparency and reproducibility in computational social science research. Documentation includes detailed preprocessing procedures, model specifications, and validation protocols to enable independent verification of findings. This commitment to open science practices aligns with contemporary standards for computational text analysis research while respecting the public nature of the analyzed communications.\u003c/p\u003e\n\u003cp\u003eCorpus Overview by Transnational Pressure Response Phases\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhase\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. of Press Conferences\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eDate Range\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eApprox. Tokens (millions)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eInternational Scrutiny Phase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eJan–Mar 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGlobal Cooperation Phase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eApr 2020–Feb 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eInternational Isolation Phase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMar 2021–Nov 2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGlobal Alignment Phase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDec 2022–Feb 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e154\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eJan 2020–Feb 2023\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.90\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eLDA Model Validation Results\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eValidation Method\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eDescription\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCoherence Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStatistical measure of topic coherence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.56 (for K=8 model)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStability Testing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRepeated model runs to check topic stability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigh overlap in top terms across runs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eExpert Review\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDomain experts validate topic-to-frame mapping\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e83.3% agreement\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eExternal Comparison\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCompare topics with policy documents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTopics aligned with policy themes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eExample of Topic-to-Frame Mapping\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eTopic (LDA Keywords)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eInterpreted Frame\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLockdown, quarantine, travel, restrictions, control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eContainment Measures Frame\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVaccine, dose, develop, trial, supply\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVaccination Campaign Frame\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEconomy, market, jobs, reopen, stimulus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEconomic Relief/Recovery Frame\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Results","content":"\u003ch2\u003eTransnational Communication Framework Evolution\u003c/h2\u003e\n\u003cp\u003eThe LDA analysis of 154 Chinese government COVID-19 press conferences (February 2020-February 2023) identified seven distinct communication frames that evolved systematically in response to transnational pressures and global health governance expectations. This longitudinal analysis reveals how China\u0026rsquo;s pandemic communication transformed from domestic crisis management to strategic global alignment, demonstrating sophisticated navigation of sovereignty-interdependence tensions in global health contexts.\u003c/p\u003e\n\u003cp\u003eSeven Communication Frames and Global Health Context\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrame\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrame Name\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eGlobal Health Governance Context\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eProminence (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e4\u003c/strong\u003e \u003cem\u003e(Continued)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrame\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrame Name\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGlobal Health Governance Context\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eProminence (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e(Continued on next page)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTransnational Health Governance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOfficial communication emphasizing integration with WHO frameworks, international cooperation protocols, and global health security contributions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEconomic-Health Nexus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEnterprise support and economic recovery within global supply chain interdependence, balancing domestic stability with international trade pressures\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHealthcare System Resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eComprehensive health service delivery demonstrating system capacity to domestic audiences while signaling health system strength to international observers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGlobal Epidemiological Standards\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCase reporting and surveillance aligned with international transparency expectations, data sharing responding to global governance demands\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVaccine Diplomacy Balance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVaccine development emphasizing technological sovereignty while engaging global distribution networks and international cooperation initiatives\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAdaptive Policy Convergence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrevention and control measures evolving toward international best practices under sustained transnational pressure for policy alignment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGlobal Supply Chain Integration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLogistics coordination within international health security frameworks, managing domestic needs with global economic interdependence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003ePhase-Specific Transnational Pressure Response Patterns\u003c/h2\u003e\n\u003cp\u003eThe analysis reveals systematic frame evolution across four phases, each characterized by distinct transnational pressure dynamics and corresponding communication adaptations that reflect China\u0026rsquo;s strategic navigation between domestic legitimacy and international expectations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInternational Scrutiny Phase (January-March 2020):\u003c/strong\u003e Healthcare System Resilience and Global Epidemiological Standards dominated as China faced unprecedented international criticism regarding transparency and accountability in global health emergency response. Communication strategy emphasized demonstrating state capacity to international observers while establishing data reporting systems aligned with WHO expectations. The government deployed 35 press conferences during this phase, representing the highest communication intensity, as authorities sought to counter international criticism while maintaining domestic crisis management credibility. Frame deployment during this phase reflected classic sovereignty protection strategies under international pressure. Healthcare System Resilience messaging (45% of communication content) emphasized medical system capacity and professional competence to counter international criticism of initial response delays. Global Epidemiological Standards messaging (25%) focused on establishing transparent reporting mechanisms aligned with international surveillance expectations, demonstrating China\u0026rsquo;s integration with global health governance frameworks despite sovereignty concerns.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGlobal Cooperation Phase (April 2020-February 2021):\u003c/strong\u003e Vaccine Diplomacy Balance and Economic-Health Nexus emerged prominently as China positioned itself as a responsible global health actor while maintaining domestic policy autonomy. This phase encompassed 42 press conferences emphasizing China\u0026rsquo;s contributions to global vaccine development and distribution networks. Communication strategy balanced international cooperation messaging with technological sovereignty assertions, reflecting strategic navigation between global integration and domestic legitimacy requirements. Vaccine Diplomacy Balance messaging (35%) emphasized China\u0026rsquo;s scientific achievements and international cooperation contributions, positioning domestic vaccine development as both national success and global public good. Economic-Health Nexus messaging (30%) integrated pandemic response with global economic recovery narratives, acknowledging economic interdependence while emphasizing China\u0026rsquo;s role in global supply chain stability. This dual emphasis reflects sophisticated understanding of how domestic health policies intersect with global economic systems.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInternational Isolation Phase (March 2021-November 2022):\u003c/strong\u003e Adaptive Policy Convergence and Healthcare System Resilience resurged as zero-COVID policies faced mounting international criticism and economic pressure. This phase featured 53 press conferences, the highest absolute number, as authorities struggled to justify policy divergence from global approaches while managing increasing international isolation pressures. Communication during this phase revealed tensions between domestic policy commitments and international pressure for convergence. Healthcare System Resilience messaging (40%) emphasized system capacity and policy effectiveness to justify continued zero-COVID approaches despite international criticism. Adaptive Policy Convergence messaging (25%) introduced flexibility language (\u0026ldquo;scientific precision,\u0026rdquo; \u0026ldquo;dynamic adjustment\u0026rdquo;) that provided linguistic foundation for subsequent policy transitions while maintaining surface policy consistency. The emergence of \u0026ldquo;optimization\u0026rdquo; terminology during late 2022 represents sophisticated semantic governance, enabling policy flexibility without explicit acknowledgment of international pressure influence. This linguistic strategy demonstrates how authoritarian communication systems can prepare for policy transitions through gradual semantic adjustment rather than direct policy reversal announcements.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGlobal Alignment Phase (December 2022-February 2023):\u003c/strong\u003e Transnational Health Governance and Economic-Health Nexus gained prominence as China rapidly converged with international endemic management approaches. This phase encompassed 24 press conferences emphasizing policy \u0026ldquo;optimization\u0026rdquo; and alignment with global health governance recommendations. Communication strategy reframed policy changes as adaptive evolution rather than external capitulation, demonstrating sophisticated crisis termination under transnational pressure. Transnational Health Governance messaging (35%) emphasized China\u0026rsquo;s integration with global health governance frameworks and alignment with WHO recommendations for endemic management. Economic-Health Nexus messaging (40%) prioritized economic recovery and international integration, reflecting recognition that continued policy divergence threatened economic interdependence relationships essential for development objectives.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003ePhase-Based Press Conference Title Keyword Evolution and Pandemic Policy Correlation (2020-2023)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003ePandemic Phase\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003ePress Conferences\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Keywords\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnique Keywords\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eDominant Keywords (Top 6)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003ePolicy Context and Correlation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunication Strategy Indicators\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e5\u003c/strong\u003e \u003cem\u003e(Continued)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePandemic Phase\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePress Conferences\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Keywords\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnique Keywords\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDominant Keywords (Top 6)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePolicy Context and Correlation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunication Strategy Indicators\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e(Continued on next page)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eInternational Scrutiny Phase\u003c/strong\u003e\u003cbr\u003e\u003cem\u003e(Jan\u0026ndash;Mar 2020)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEpidemic (疫情), Situation (情况), Prevention Control (防控), Guarantee (保障), Enterprise (企业), Work Resumption (复工)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWuhan lockdown implementation, national emergency response activation, initial economic support measures for enterprises, comprehensive crisis mobilization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCrisis emergence communication: Highest vocabulary diversity, comprehensive response messaging, emphasis on situation control and enterprise support\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGlobal Cooperation Phase\u003c/strong\u003e\u003cbr\u003e\u003cem\u003e(Apr 2020\u0026ndash;Feb 2021)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e258\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEpidemic (疫情), Prevention Control (防控), COVID-19 (新冠), Vaccine (疫苗), Pneumonia (肺炎), Medical (医疗)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVaccine development acceleration, mass vaccination campaign launch, gradual reopening preparations, expert consultation integration, normalization planning initiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVaccine transition communication: Scientific achievement emphasis, vaccination infrastructure development, medical system strengthening, expert authority integration\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eInternational Isolation Phase\u003c/strong\u003e\u003cbr\u003e\u003cem\u003e(Mar 2021\u0026ndash;Nov 2022)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e429\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEpidemic (疫情), Prevention Control (防控), Vaccine (疫苗), Vaccination (接种), Scientific (科学), Precision (精准)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eZero-COVID policy intensification, Shanghai lockdown implementation, scientific precision policy introduction, Delta and Omicron variant responses, strict enforcement measures\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIntensification communication: Highest frequency period, enforcement language dominance, scientific precision terminology adoption, policy justification focus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGlobal Alignment Phase\u003c/strong\u003e\u003cbr\u003e\u003cem\u003e(Dec 2022\u0026ndash;Feb 2023)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKey/Priority (重点), Epidemic (疫情), Prevention Control (防控), Population (人群), Medical (医疗), Guarantee (保障), Optimization (优化)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eZero-COVID policy relaxation, optimization measures introduction, endemic transition management, vulnerable population focus, medical service enhancement, Spring Festival normalization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEndemic adaptation communication: Targeted population focus, optimization terminology emergence, medical service emphasis, reduced epidemic emphasis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Discussion","content":"\u003ch2\u003eTheoretical Contributions: Challenging Linear Crisis Models and Authoritarian Frame Dynamics\u003c/h2\u003e\n\u003cp\u003eThis study makes two pivotal theoretical contributions that fundamentally reconceptualize crisis communication dynamics in extended emergencies. First, the empirical analysis reveals a \u003cstrong\u003ecyclical frame reinforcement model\u003c/strong\u003e that directly challenges and modifies the linear progression assumptions that have dominated crisis communication theory since Coombs’ foundational work. Traditional crisis lifecycle models conceptualize crisis communication as unidirectional temporal development—progressing sequentially from pre-crisis awareness through acute crisis response to post-crisis recovery—with the implicit assumption that communication strategies evolve forward without returning to previous phases . This linear paradigm treats crisis communication as a problem-solving sequence where each phase builds upon the previous one, ultimately culminating in resolution and organizational learning. The Chinese COVID-19 data fundamentally contradicts this linear assumption, revealing instead a recursive pattern where frames undergo strategic cyclical intensification and redeployment. The empirical evidence demonstrates that crisis communication in extended emergencies operates through what can be termed “spiral progression”—a dynamic where previously deployed frames are not abandoned but rather stored as strategic resources for future reactivation.\u003c/p\u003e\n\u003cp\u003eThis cyclical mechanism—where “retired” frames are strategically reactivated, modified, and redeployed for new circumstances—represents a fundamental theoretical advancement that requires crisis communication models to account for recursive rather than linear temporal dynamics. The theoretical implications extend beyond simple model modification to challenge core assumptions about crisis narrative development. Where traditional models assume progressive frame abandonment as crises evolve, the cyclical reinforcement model reveals that effective extended crisis communication operates through iterative adaptation cycles that treat previous frames as renewable strategic assets. This finding necessitates theoretical frameworks that model recursive intensification as a core feature of protracted crisis management, fundamentally altering how scholars conceptualize the relationship between time, narrative evolution, and communication effectiveness in extended emergencies.\u003c/p\u003e\n\u003cp\u003eThe \u003cstrong\u003ecyclical frame reinforcement model\u003c/strong\u003e proposed in this study foregrounds the deliberate, strategic redeployment of previously shelved \u003cem\u003eframes\u003c/em\u003e rather than the involuntary re-entry into operational phases. It explains how communicators actively revive earlier discursive packages—often in altered form—to maintain legitimacy or mobilize compliance even when the material threat profile has changed. This distinction highlights the unique contribution of the present research: it shifts analytical focus from organizational process loops to rhetorical strategy cycles, revealing how narrative tools themselves become resources that can be stored, re-activated, and reconfigured across protracted emergencies.\u003c/p\u003e\n\u003cp\u003eSecond, the analysis identifies \u003cstrong\u003esemantic governance\u003c/strong\u003e as a distinctive mechanism of authoritarian crisis communication that extends framing theory into the domain of regime legitimacy maintenance. Unlike democratic contexts where policy reversals typically require explicit acknowledgment and justification due to pluralistic discourse environments, the Chinese case demonstrates how controlled information ecosystems enable sophisticated linguistic engineering to preserve governmental credibility during major policy transitions. The transition from “zero-COVID” to “coexistence” messaging exemplifies semantic governance in action: rather than acknowledging policy failure, authorities employed strategic euphemism (“optimization”), temporal reframing (“new phase”), and victory narratives (“decisive success”) to transform policy reversal into adaptive evolution. This linguistic management represents a form of soft power governance where semantic control becomes a mechanism for exercising authority over public perception, enabling regimes to navigate policy contradictions without appearing to falter. The theoretical significance lies in demonstrating how authoritarian communication systems can leverage discourse monopoly to achieve frame transformation impossible in competitive information environments. This insight expands framing theory beyond its traditional focus on competitive discourse dynamics (Chong and Druckman 2007) to encompass how controlled information systems generate unique opportunities for strategic narrative management that preserve legitimacy while enabling policy adaptation.\u003c/p\u003e\n\u003cp\u003eThe analysis reveals that \"semantic governance\" in authoritarian contexts transcends mere administrative control over information flows, constituting instead a systematic \u003cem\u003ediscursive capacity\u003c/em\u003e for meaning construction . Through the strategic establishment of acceptable semantic boundaries, the manipulation of keyword emotional orientations, and the systematic \"addition, deletion, and substitution\" of core vocabulary across different crisis phases, governmental actors achieve the reallocation of public emotions and attribution logic without substantially altering underlying policy objectives. This monopolization of symbolic resources enables regimes to rewrite potential policy failures—such as the termination of zero-COVID strategies—as strategic upgrades, thereby achieving what might be termed \"continuity through policy discontinuity\" . In contrast to democratic contexts that rely on public deliberation to modify narratives, semantic governance demonstrates an alternative pathway for legitimacy maintenance through \u003cem\u003ediscursive recoding\u003c/em\u003e rather than \u003cem\u003ediscursive competition\u003c/em\u003e . Semantic governance contributes two distinctive insights to crisis communication scholarship. First, the \u003cstrong\u003enarrative resilience mechanism\u003c/strong\u003e operates through gradual semantic adjustments—such as the progression from \"zero-COVID\" to \"optimization\" to \"coexistence\"—enabling authorities to absorb external shocks while preserving overarching narrative frameworks . This demonstrates superior narrative flexibility compared to simple media censorship, revealing sophisticated discursive elasticity that maintains interpretive coherence despite policy volatility . Second, semantic governance functions as a \u003cstrong\u003elegitimacy transformation bridge\u003c/strong\u003e, connecting performance-based legitimacy with performative legitimacy through the intermediary mechanism of \"narrative legitimacy\" . This enables regimes to maintain psychological dominance over public perception through semantic recoding when performance indicators falter, suggesting that traditional crisis lifecycle models require supplementation with a pervasive \"semantic adaptation\" component . Such theoretical expansion explains how authoritarian systems accomplish crisis narrative self-repair and reproduction through controlled discourse systems in the absence of institutionalized accountability mechanisms.\u003c/p\u003e\n\u003ch2\u003eTheoretical Positioning: Dialogue with International Crisis Communication Scholarship\u003c/h2\u003e\n\u003cp\u003eThe empirical findings from this Chinese case study necessitate theoretical positioning within the broader field of crisis communication. By revealing cyclical frame reinforcement and semantic governance dynamics, this research dialogues with international crisis communication scholarship to both challenge and enrich existing models. Firstly, the evidence of recursive frame deployment invites a reconsideration of widely accepted crisis stages models beyond Chinese or authoritarian contexts. While cyclicality was observed in China’s crisis narrative, future research should examine whether elements of frame recycling appear in protracted crises elsewhere. Integrating our cyclical reinforcement model with models like (\u003cstrong\u003ecoombs2021recycle?\u003c/strong\u003e)’s recycle–recrisis could yield a more universal understanding of crisis communication patterns when crises are prolonged or recurring. Secondly, the concept of semantic governance underscores how political context can fundamentally alter crisis communication mechanisms. In democratic settings, crisis communication effectiveness is often tied to managing a contested information environment, as stakeholders publicly debate narratives (Chong and Druckman 2007). The Chinese case suggests that in controlled media environments, narrative flexibility can substitute for public debate. Scholars should explore to what extent semantic governance tactics—like euphemisms or strategic re-framings—are present or viable in hybrid regimes or even democracies under certain conditions (e.g., wartime censorship or emergency laws). Thirdly, by focusing on how global pressures mediate domestic communication (and vice versa), this study aligns with calls for a more internationalized crisis communication theory (Hajer, Wassila, and Moufida 2015). Our findings support the notion that crisis communication strategies must be analyzed within a multi-level governance context, acknowledging that global interdependence and transnational norms increasingly shape national narratives. This Chinese case thus contributes a concrete example of how global forces (WHO guidelines, international opinion, etc.) can be internalized and linguistically managed within state narratives. Finally, the research highlights an interplay between performance legitimacy and narrative legitimacy, resonating with frameworks from political science on authoritarian resilience (Holbig 2023). It suggests crisis communication scholars should incorporate insights from comparative politics, recognizing that the goals and methods of crisis framing may differ across regimes not only in degree but in kind. By engaging with interdisciplinary perspectives, the refined theoretical constructs proposed here—cyclical frame reinforcement and semantic governance—can be tested and elaborated in varied socio-political contexts, advancing a more globally attuned crisis communication scholarship.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis longitudinal frame analysis of Chinese government COVID-19 press conferences (2020-2023) has provided comprehensive insights into crisis communication dynamics during an extended global health emergency. Through computational topic modeling and qualitative interpretation, the study documented systematic frame evolution across four distinct pandemic phases, revealing sophisticated governmental communication strategies that adapted to changing epidemiological, economic, and social conditions.\u003c/p\u003e\n\u003cp\u003eThe study also points to how government public health messaging served a critical function in legitimizing stringent interventions, sustaining vaccine uptake, and gradually guiding citizens toward post-crisis normalcy. Communication strategies often integrated moral appeals, scientific justifications, and nationalistic or war-like metaphors to anchor public compliance and deter misinformation. This multi-frame approach underscores the complexity of large-scale, prolonged crisis communication, where no single narrative can continuously suffice.\u003c/p\u003e\n\u003cp\u003eWhile this study provides comprehensive analysis of Chinese government COVID-19 crisis communication, several limitations merit acknowledgment alongside future research directions that can extend understanding of crisis framing dynamics. Methodologically, the LDA approach, while enabling systematic analysis of large textual corpora, may overlook nuanced rhetorical strategies, irony, or culturally-specific metaphors significant in Chinese political discourse. The exclusive focus on official press conferences, though justified by their authoritative status, excludes other communication channels such as local government messaging, social media posts, and policy documents that may reveal different framing strategies or internal tensions within governmental messaging.\u003c/p\u003e\n\u003cp\u003eFuture research should prioritize comparative analysis across multiple political systems and cultural contexts to validate and refine theoretical insights, enabling identification of universal versus system-specific patterns in crisis framing strategies. Reception-focused research represents a critical direction, requiring mixed-methods approaches combining computational analysis of social media responses, survey research across demographic segments, and ethnographic investigation of community frame interpretation.\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge the support provided by the data collection platforms and the valuable insights contributed by the research participants. Special thanks to the reviewers for their constructive feedback that significantly improved this manuscript.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: This research has not got any funding.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eConflict of interest/Competing interests\u003c/strong\u003e: The authors declare no competing interests.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e: All data are drawn from publicly available government sources; no personal information is involved. The study complies with the PRC Regulations on Open Government Information and academic integrity standards.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e: Yes.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eData availability\u003c/strong\u003e: The dataset analyzed during the current study is available from the corresponding author on reasonable request.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eMaterials availability\u003c/strong\u003e: Not applicable.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e: The analysis code used in this study is available from the corresponding author on reasonable request.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e: All authors contributed equally to the conception, design, analysis, and writing of this manuscript.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBenziman, Yuval. 2020. \u0026ldquo;\u0026lsquo;Winning\u0026rsquo; the \u0026lsquo;Battle\u0026rsquo; and \u0026lsquo;Beating\u0026rsquo; the COVID-19 \u0026lsquo;Enemy\u0026rsquo;: Leaders\u0026rsquo; Use of War Frames to Define the Pandemic.\u0026rdquo; \u003cem\u003ePeace and Conflict: Journal of Peace Psychology\u003c/em\u003e 26 (3): 247.\u003c/li\u003e\n\u003cli\u003eBernard, Natalie Reyes, Abdul Basit, Ernesta Sofija, Hai Phung, Jessica Lee, Shannon Rutherford, Bernadette Sebar, Neil Harris, Dung Phung, and Nicola Wiseman. 2021. \u0026ldquo;Analysis of Crisis Communication by the Prime Minister of Australia During the COVID-19 Pandemic.\u0026rdquo; \u003cem\u003eInternational Journal of Disaster Risk Reduction\u003c/em\u003e 62: 102375.\u003c/li\u003e\n\u003cli\u003eBlei, David M. 2012. \u0026ldquo;Probabilistic Topic Models.\u0026rdquo; \u003cem\u003eCommunications of the ACM\u003c/em\u003e 55 (4): 77\u0026ndash;84. https://doi.org/10.1145/2133806.2133826\u003c/li\u003e\n\u003cli\u003eBlei, David M, Andrew Y Ng, and Michael I Jordan. 2003. \u0026ldquo;Latent Dirichlet Allocation.\u0026rdquo; \u003cem\u003eJournal of Machine Learning Research\u003c/em\u003e 3 (Jan): 993\u0026ndash;1022.\u003c/li\u003e\n\u003cli\u003eChan, Chi Kit, and Anthony Ying Him Fung. 2021. \u0026ldquo;From Soft Power to Sharp Power: China\u0026rsquo;s Media Image in Hong Kong\u0026rsquo;s Health Crises from 2003 to 2020.\u0026rdquo; \u003cem\u003eGlobal Media and China\u003c/em\u003e 6 (1): 62\u0026ndash;76.\u003c/li\u003e\n\u003cli\u003eChapman, Connor M, and DeMond Shondell Miller. 2020. \u0026ldquo;From Metaphor to Militarized Response: The Social Implications of \u0026lsquo;We Are at War with COVID-19\u0026rsquo;\u0026ndash;Crisis, Disasters, and Pandemics yet to Come.\u0026rdquo; \u003cem\u003eInternational Journal of Sociology and Social Policy\u003c/em\u003e 40 (9/10): 1107\u0026ndash;24.\u003c/li\u003e\n\u003cli\u003eChen, Qiang, Chen Min, Wei Zhang, Ge Wang, Xiaoyue Ma, and Richard Evans. 2020. \u0026ldquo;Unpacking the Black Box: How to Promote Citizen Engagement Through Government Social Media During the COVID-19 Crisis.\u0026rdquo; \u003cem\u003eComputers in Human Behavior\u003c/em\u003e 110: 106380.\u003c/li\u003e\n\u003cli\u003eChong, Dennis, and James N Druckman. 2007. \u0026ldquo;Framing Theory.\u0026rdquo; \u003cem\u003eAnnu. Rev. Polit. Sci.\u003c/em\u003e 10 (1): 103\u0026ndash;26.\u003c/li\u003e\n\u003cli\u003eCoombs, W Timothy, and Sherry Jean Holladay. 2014. \u0026ldquo;How Publics React to Crisis Communication Efforts: Comparing Crisis Response Reactions Across Sub-Arenas.\u0026rdquo; \u003cem\u003eJournal of Communication Management\u003c/em\u003e 18 (1): 40\u0026ndash;57.\u003c/li\u003e\n\u003cli\u003eDada, Sara, Heather Battles, Caitlin Pilbeam, Bhagteshwar Singh, Tom Solomon, and Nina Gobat. 2021. \u0026ldquo;Learning from the Past and Present: Social Science Implications for COVID-19 Immunity-Based Documentation.\u0026rdquo; \u003cem\u003eHumanities and Social Sciences Communications\u003c/em\u003e 8 (1).\u003c/li\u003e\n\u003cli\u003eDau, Duc, and Katie Ellis. 2023. \u0026ldquo;From Bondi to Fairfield: NSW COVID-19 Press Conferences, Health Messaging, and Social Inequality.\u0026rdquo; \u003cem\u003eMedia International Australia\u003c/em\u003e 188 (1): 34\u0026ndash;51.\u003c/li\u003e\n\u003cli\u003eEntman, Robert M. 1993. \u0026ldquo;Framing: Toward Clarification of a Fractured Paradigm.\u0026rdquo; \u003cem\u003eJournal of Communication\u003c/em\u003e 43 (4): 51\u0026ndash;58.\u003c/li\u003e\n\u003cli\u003eGoffman, Erving. 1974. \u003cem\u003eFrame Analysis: An Essay on the Organization of Experience.\u003c/em\u003e Harvard University Press.\u003c/li\u003e\n\u003cli\u003eGui, Lili. 2021. \u0026ldquo;Media Framing of Fighting COVID-19 in China.\u0026rdquo; \u003cem\u003eSociology of Health \u0026amp; Illness\u003c/em\u003e 43 (4): 966\u0026ndash;70.\u003c/li\u003e\n\u003cli\u003eHajer, Degachi, Chagra Wassila, and Ksouri Moufida. 2015. \u0026ldquo;Global Optimization Method for Min-Max MPC Based on Wiener and Hammerstein Model.\u0026rdquo; In \u003cem\u003e2015 7th International Conference on Modelling, Identification and Control (ICMIC)\u003c/em\u003e, 1\u0026ndash;6. IEEE.\u003c/li\u003e\n\u003cli\u003eHarper, Craig A, Liam P Satchell, Dean Fido, and Robert D Latzman. 2021. \u0026ldquo;Functional Fear Predicts Public Health Compliance in the COVID-19 Pandemic.\u0026rdquo; \u003cem\u003eInternational Journal of Mental Health and Addiction\u003c/em\u003e 19 (5): 1875\u0026ndash;88.\u003c/li\u003e\n\u003cli\u003eHe, Alex Jingwei, Yuda Shi, and Hongdou Liu. 2020. \u0026ldquo;Crisis Governance, Chinese Style: Distinctive Features of China\u0026rsquo;s Response to the Covid-19 Pandemic.\u0026rdquo; \u003cem\u003ePolicy Design and Practice\u003c/em\u003e 3 (3): 242\u0026ndash;58.\u003c/li\u003e\n\u003cli\u003eHolbig, Heike. 2023. \u0026ldquo;China\u0026rsquo;s Response to the COVID-19 Pandemic: Navigating Internal and External Challenges.\u0026rdquo; In \u003cem\u003eDemocracy, State Capacity and the Governance of COVID-19 in Asia-Oceania\u003c/em\u003e, 244\u0026ndash;66. Routledge.\u003c/li\u003e\n\u003cli\u003eHuang, Chaolin, Yeming Wang, Xingwang Li, Lili Ren, Jianping Zhao, Yi Hu, Li Zhang, et al. 2020. \u0026ldquo;Clinical Features of Patients Infected with 2019 Novel Coronavirus in Wuhan, China.\u0026rdquo; \u003cem\u003eThe Lancet\u003c/em\u003e 395 (10223): 497\u0026ndash;506.\u003c/li\u003e\n\u003cli\u003eJacobs, Thomas, and Robin Tsch\u0026ouml;tschel. 2019. \u0026ldquo;Topic Models Meet Discourse Analysis: A Quantitative Tool for a Qualitative Approach.\u0026rdquo; \u003cem\u003eInternational Journal of Social Research Methodology\u003c/em\u003e 22 (5): 469\u0026ndash;85.\u003c/li\u003e\n\u003cli\u003eJacobsen, Kathryn H, A Alonso Aguirre, Charles L Bailey, Ancha V Baranova, Andrew T Crooks, Arie Croitoru, Paul L Delamater, et al. 2016. \u0026ldquo;Lessons from the Ebola Outbreak: Action Items for Emerging Infectious Disease Preparedness and Response.\u0026rdquo; \u003cem\u003eEcoHealth\u003c/em\u003e 13: 200\u0026ndash;212.\u003c/li\u003e\n\u003cli\u003eKickbusch, Ilona, Graham Lister, Michaela Told, and Nick Drager. 2013. \u003cem\u003eGlobal Health Diplomacy: Concepts, Issues, Actors, Instruments, Fora and Cases\u003c/em\u003e. Springer.\u003c/li\u003e\n\u003cli\u003eKim, Do Kyun David, and Gary L Kreps. 2020. \u0026ldquo;An Analysis of Government Communication in the United States During the COVID-19 Pandemic: Recommendations for Effective Government Health Risk Communication.\u0026rdquo; \u003cem\u003eWorld Medical \u0026amp; Health Policy\u003c/em\u003e 12 (4): 398\u0026ndash;412.\u003c/li\u003e\n\u003cli\u003eKneuer, Marianne, and Stefan Wallaschek. 2023. \u0026ldquo;Framing COVID-19: Public Leadership and Crisis Communication by Chancellor Angela Merkel During the Pandemic in 2020.\u0026rdquo; \u003cem\u003eGerman Politics\u003c/em\u003e 32 (4): 686\u0026ndash;709.\u003c/li\u003e\n\u003cli\u003eLabont\u0026eacute;, Ronald, Katia Mohindra, and Ted Schrecker. 2011. \u0026ldquo;The Growing Impact of Globalization for Health and Public Health Practice.\u0026rdquo; \u003cem\u003eAnnual Review of Public Health\u003c/em\u003e 32 (1): 263\u0026ndash;83.\u003c/li\u003e\n\u003cli\u003eLyu, Lin, Lily Suriani Binti Mohd Arif, and Ruzanna Binti Shahrin. 2024. \u0026ldquo;Analysis of Pandemic Reporting Framework of Mainstream New Media Based on the Reports of Typical Mainstream Media Wechat Official Account.\u0026rdquo; \u003cem\u003eStudies in Media and Communication\u003c/em\u003e 12 (1): 79\u0026ndash;89.\u003c/li\u003e\n\u003cli\u003eMacKay, Melissa, Taylor Colangeli, Abhinand Thaivalappil, Ariana Del Bianco, Jennifer McWhirter, and Andrew Papadopoulos. 2022. \u0026ldquo;A Review and Analysis of the Literature on Public Health Emergency Communication Practices.\u0026rdquo; \u003cem\u003eJournal of Community Health\u003c/em\u003e, 1\u0026ndash;13.\u003c/li\u003e\n\u003cli\u003eMaier, Daniel, Annie Waldherr, Peter Miltner, Gregor Wiedemann, Andreas Niekler, Alexa Keinert, Barbara Pfetsch, et al. 2021. \u0026ldquo;Applying LDA Topic Modeling in Communication Research: Toward a Valid and Reliable Methodology.\u0026rdquo; In \u003cem\u003eComputational Methods for Communication Science\u003c/em\u003e, 13\u0026ndash;38. Routledge.\u003c/li\u003e\n\u003cli\u003eMoon, Suerie, John-Arne R\u0026oslash;ttingen, and Julio Frenk. 2017. \u0026ldquo;Global Public Goods for Health: Weaknesses and Opportunities in the Global Health System.\u0026rdquo; \u003cem\u003eHealth Economics, Policy and Law\u003c/em\u003e 12 (2): 195\u0026ndash;205.\u003c/li\u003e\n\u003cli\u003eNing, Peishan, Peixia Cheng, Jie Li, Ming Zheng, David C Schwebel, Yang Yang, Peng Lu, Li Mengdi, Zhuo Zhang, and Guoqing Hu. 2021. \u0026ldquo;COVID-19\u0026ndash;Related Rumor Content, Transmission, and Clarification Strategies in China: Descriptive Study.\u0026rdquo; \u003cem\u003eJournal of Medical Internet Research\u003c/em\u003e 23 (12): e27339.\u003c/li\u003e\n\u003cli\u003eSeeger, Matthew W. 2006. \u0026ldquo;Best Practices in Crisis Communication: An Expert Panel Process.\u0026rdquo; \u003cem\u003eJournal of Applied Communication Research\u003c/em\u003e 34 (3): 232\u0026ndash;44.\u003c/li\u003e\n\u003cli\u003eWatkins, Daryl V, and Aaron D Clevenger. 2021. \u0026ldquo;US Political Leadership and Crisis Communication During COVID-19.\u0026rdquo; \u003cem\u003eCogent Social Sciences\u003c/em\u003e 7 (1): 1901365.\u003c/li\u003e\n\u003cli\u003eXie, Qihui, Yanan Xue, and Zhuojun Zhao. 2022. \u0026ldquo;Understanding the Scientific Topics in the Chinese Government\u0026rsquo;s Communication about COVID-19: An LDA Approach.\u0026rdquo; \u003cem\u003eSustainability\u003c/em\u003e 14 (15): 9614.\u003c/li\u003e\n\u003cli\u003eZhou, Cheng, Haoxin Xiu, Yuqiu Wang, and Xinyao Yu. 2021. \u0026ldquo;Characterizing the Dissemination of Misinformation on Social Media in Health Emergencies: An Empirical Study Based on COVID-19.\u0026rdquo; \u003cem\u003eInformation Processing \u0026amp; Management\u003c/em\u003e 58 (4): 102554.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"globalization-and-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"glah","sideBox":"Learn more about [Globalization and Health](https://globalizationandhealth.biomedcentral.com/)","snPcode":"12992","submissionUrl":"https://submission.nature.com/new-submission/12992/3","title":"Globalization and Health","twitterHandle":"@GHJournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Crisis Communication, Framing Theory, COVID-19, Government Communication, Topic Modeling, Pandemic Response","lastPublishedDoi":"10.21203/rs.3.rs-7117519/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7117519/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The COVID-19 pandemic radically reshaped global communication dynamics, compelling governments to deliver frequent updates on infection rates, public health protocols, and evolving scientific knowledge. This study examines how the Chinese government, through its official press conferences, established and maintained specific frames during the COVID-19 pandemic across four distinct phases from 2020 to 2023. Using Latent Dirichlet Allocation (LDA) topic modeling on 154 press conference transcripts, we identified seven distinct communication frames. The analysis reveals a sophisticated cyclical frame reinforcement model that challenges traditional linear crisis communication theories, demonstrating how authoritarian communication systems can strategically reactivate previously effective frames for new policy objectives. The study contributes to crisis communication theory by identifying semantic governance as a distinctive mechanism for maintaining regime legitimacy during major policy transitions, enabling governments to transform policy reversals into adaptive evolution through strategic linguistic engineering.","manuscriptTitle":"From Zero-COVID to Global Alignment: Transnational Pressures and China’s Pandemic Communication Transformation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-04 08:06:47","doi":"10.21203/rs.3.rs-7117519/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-10T20:36:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-13T16:19:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"87524504318441103848015009314332721427","date":"2025-08-06T19:06:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"50924252712391442322782623678222662855","date":"2025-08-01T07:14:31+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-30T13:58:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-28T17:23:14+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-28T17:22:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"Globalization and Health","date":"2025-07-14T06:12:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"globalization-and-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"glah","sideBox":"Learn more about [Globalization and Health](https://globalizationandhealth.biomedcentral.com/)","snPcode":"12992","submissionUrl":"https://submission.nature.com/new-submission/12992/3","title":"Globalization and Health","twitterHandle":"@GHJournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a9f8ec4b-d160-42c2-a73d-e0b3414ca1f3","owner":[],"postedDate":"August 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-06T13:54:58+00:00","versionOfRecord":{"articleIdentity":"rs-7117519","link":"https://doi.org/10.1186/s12992-025-01155-y","journal":{"identity":"globalization-and-health","isVorOnly":false,"title":"Globalization and Health"},"publishedOn":"2025-11-04 00:00:00","publishedOnDateReadable":"November 4th, 2025"},"versionCreatedAt":"2025-08-04 08:06:47","video":"","vorDoi":"10.1186/s12992-025-01155-y","vorDoiUrl":"https://doi.org/10.1186/s12992-025-01155-y","workflowStages":[]},"version":"v1","identity":"rs-7117519","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7117519","identity":"rs-7117519","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}