Local Media–Derived Indicators for Monitoring Municipal Solid Waste Governance: A Text-Mining Assessment

Local Media–Derived Indicators for Monitoring Municipal Solid Waste Governance: A Text-Mining Assessment | 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 Research Article Local Media–Derived Indicators for Monitoring Municipal Solid Waste Governance: A Text-Mining Assessment Reza Nemati, Alireza Bagheri Resaei, Narges Hakimi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8525042/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Rapid urbanization has revealed significant limitations in traditional municipal solid waste (MSW) monitoring systems, especially those focusing primarily on technical and infrastructural indicators. While these approaches address operational aspects, they often overlook key dimensions like governance performance, service reliability, and public response. These aspects are critical for effective waste management but are less systematically monitored. Local digital media discourse presents an underutilized resource for real-time monitoring of these qualitative dimensions. This study conceptualizes local digital media discourse as a perception-based monitoring tool for environmental monitoring in MSW governance. A descriptive–analytical text-mining design was adopted to systematically extract, structure, and interpret monitoring indicators embedded in local media content related to MSW management. Five monitoring-relevant themes were identified, each reflecting distinct dimensions of environmental risk and governance performance: unsanitary waste disposal and leachate impacts; limitations in recycling and composting infrastructure; contractor performance deficiencies; waste picking activities; and public dissatisfaction with municipal services. Negative sentiments, particularly anger (32%) and concern (23%), were prominent, alongside expressions of hope (18%), satisfaction (12%), and neutral content (15%). Notably, critical narratives frequently co-occurred with concrete, improvement-oriented suggestions. The analysis indicates that local media content reflects aspects of governance performance and service-related concerns that are not routinely documented in technical MSW datasets. These signals appear particularly relevant in contexts where formal monitoring is fragmented or delayed. Environmental monitoring municipal solid waste management text mining media-derived indicators urban environmental governance media-based monitoring Figures Figure 1 Figure 2 Introduction Rapid urbanization, coupled with escalating environmental pressures, has intensified the complexity of municipal solid waste (MSW) management worldwide, with consequences extending beyond environmental degradation to public health risks and the reliability of urban service provision. Inadequate waste collection, unsanitary disposal practices, and uncontrolled activities such as open burning contribute to air, soil, and water contamination, thereby exacerbating infectious, respiratory, and cardiovascular health outcomes (Ferronato & Torretta, 2019 ; Ncube et al., 2017 ; Zhang et al., 2024 ). These challenges underscore the need not only for improved technical interventions but also for effective monitoring approaches capable of capturing system performance and emerging risks within urban waste governance Collective participation plays a critical role in municipal solid waste governance by shaping transparency, accountability, and public confidence in decision-making processes. Beyond its normative importance, participation also generates observable signals through public communication, feedback, and collective responses to waste management practices. The engagement of community members and institutional actors therefore constitutes not only a governance objective but also a source of information through which the performance and legitimacy of MSW systems can be assessed. (Hinds & Sparks, 2008 ; Huang et al., 2023 ; Youngquist et al., 2015 ). Despite advances in technical monitoring of municipal solid waste systems, existing assessment approaches often remain narrowly focused on operational and infrastructural indicators, such as collection coverage, disposal capacity, and treatment efficiency (Cervantes et al., 2018 ; Sasahara et al., 2024 ; Wilson et al., 2015 ). While these metrics are essential, they provide limited insight into governance performance, institutional responsiveness, and public-facing dimensions of waste management (Rodić & Wilson, 2017 ). As a result, early signals of service failure, declining trust, or emerging environmental risks may remain undetected until they manifest as systemic problems (Scheinberg et al., 2010 ). This limitation highlights the need for complementary monitoring approaches capable of capturing qualitative, real-time information related to governance processes and public experience (Rodić & Wilson, 2017 ). Effective municipal solid waste management is increasingly recognized as a governance challenge rather than a purely technical one. Although investments in collection systems, treatment facilities, and disposal technologies remain indispensable, their long-term effectiveness is closely tied to public engagement, behavioral responses, and institutional accountability (Ferronato & Torretta, 2019 ). Empirical evidence suggests that even technically advanced waste systems may fail to deliver sustained environmental and health benefits when community involvement is fragmented or weak (Kuang & Lin, 2021 ). These observations have prompted a growing emphasis on governance frameworks that incorporate social, behavioral, and communicative processes—dimensions that shape how waste management policies are interpreted, contested, and enacted in practice. Communication-oriented interventions, including awareness campaigns, environmental education, and participatory feedback mechanisms, have been associated with measurable changes in waste-related behaviors such as source separation, recycling, and composting (Konstantinidou et al., 2024 ). Beyond their instrumental role in promoting compliance, these interventions generate continuous streams of public communication through which attitudes, expectations, and responses to municipal waste services are expressed. When embedded within broader governance frameworks, such communicative processes contribute to the formation and maintenance of public trust and civic responsibility over time (Kuang & Lin, 2021 ), while simultaneously offering observable signals relevant to the assessment of MSW governance performance. In many rapidly urbanizing contexts, municipal solid waste management continues to be shaped by structural and operational constraints, including limitations in treatment capacity, service coverage, and regulatory enforcement (Zhang et al., 2025 ). Under such conditions, public behavior and collective responses play a decisive role in shaping waste generation, separation, and disposal practices(Chen et al., 2020 ; Sasahara et al., 2024 ), thereby amplifying the relevance of communication processes within waste governance(Pan et al., 2023 ). The expansion of digital platforms and locally oriented online media has transformed urban information environments, enabling continuous, publicly accessible exchanges through which waste-related experiences, concerns, and evaluations are expressed (Khan et al., 2024 ). These local media spaces increasingly function as arenas where governance performance is observed, discussed, and implicitly assessed (Khan et al., 2024 ). International evidence from diverse contexts—including China, Indonesia, and Australia—demonstrates that local and community-based media can play a meaningful role in shaping public participation in recycling initiatives, food waste reduction, and environmentally responsible behaviors (Jiang et al., 2021 ; Shittu et al., 2024 ; Yandri et al., 2023 ). Beyond their communicative function, these platforms increasingly generate real-time, perception-based information that reflects public responses to municipal services and governance practices. Such characteristics position local media as potentially valuable, yet underutilized, sources of indirect monitoring data for MSW management. In practical monitoring terms, these findings indicate, discourse within local digital media may complement conventional technical indicators by capturing qualitative signals related to environmental risk, service performance, institutional accountability, and public trust. Analyzing these narratives offers a means to identify emerging governance challenges and societal concerns that are often overlooked by infrastructure-focused assessments. As such, media-based analysis may enhance the responsiveness and contextual sensitivity of environmental governance frameworks (Ghermandi et al., 2023 ). Text-mining approaches provide a systematic and scalable means of extracting patterns from large volumes of unstructured media content. By enabling the quantitative identification of dominant themes and sentiment orientations, these methods facilitate the translation of narrative discourse into structured, monitoring-relevant information (Bing, 2012 ; DiMaggio et al., 2013 ; Grimmer & Stewart, 2013 ). In contexts where large-scale surveys or participatory assessments are limited by logistical or financial constraints, computational analysis of publicly accessible digital media offers a reproducible and ethically viable alternative for inferring public perceptions and engagement (Zolnoori et al., 2019 ). Despite growing international interest in media-informed environmental governance, research on MSW management in Iran has largely emphasized technical, infrastructural, and operational dimensions. In medium-sized Iranian cities such as Saveh, municipal solid waste services are frequently evaluated by citizens through local digital media rather than formal reporting channels. The communicative and monitoring potential of local media—particularly their capacity to reflect citizen participation, dissatisfaction, and trust in municipal waste governance—remains insufficiently examined. This gap is especially consequential in medium-sized urban settings, where persistent MSW challenges coexist with active local digital media ecosystems. In such contexts, local media may simultaneously function as watchdogs that highlight governance deficiencies and as facilitators that promote constructive engagement and pro-environmental behavior (Wu et al., 2021 ; Zhang et al., 2024 ). In this study, local media are conceptualized as publicly accessible digital news outlets and community-oriented social media channels operating at the city scale. Using a descriptive–analytical text-mining framework, the study examines how discourse published across local digital platforms between 2022 and 2025 reflects public participation and perceived governance performance in MSW management. By integrating computational text analysis with an environmental monitoring and public health perspective, the research contributes empirical evidence on the utility of media-based indicators for strengthening transparency, participation, and adaptive governance in municipal solid waste systems. To ensure an explicitly analytical and monitoring-oriented focus, this study addresses the following research questions: RQ1. Can local digital media discourse be operationalized into reproducible indicators relevant to municipal solid waste (MSW) monitoring? RQ2. Which MSW performance dimensions—environmental risk, service reliability, or governance performance—are most prominently reflected in media-derived indicators? RQ3. Do temporal variations in media-derived indicators exhibit characteristics consistent with potential early-warning signals for MSW governance stress? Materials and Methods Study Design This study was designed within the context of an environmental monitoring and assessment framework to address recognized limitations of conventional MSW monitoring systems. In this study, monitoring is operationally defined as the systematic detection of recurrent, publicly observable signals that indicate deviations, stress, or risk within MSW systems, prior to their formal registration in technical or regulatory datasets. Traditional MSW monitoring largely relies on technical and operational indicators, which often fail to capture governance performance, service reliability, and public response in a timely manner (Scheinberg et al., 2010 ; Wilson et al., 2015 ). To complement these limitations, the present study conceptualizes local digital media discourse as a perception-based monitoring layer capable of generating qualitative indicators relevant to MSW governance. A descriptive–analytical text-mining design was adopted to systematically extract, structure, and interpret monitoring indicators embedded in local media content (Rivera et al., 2014 ; Zolnoori et al., 2019 ). Within this framework, media discourse is treated not merely as communication output, but as an observational data stream reflecting public encounters with environmental conditions, service disruptions, and institutional responsiveness. The methodological framework comprised four sequential and interrelated stages: data collection, data extraction, text preprocessing, and analytical modeling. This structure enabled the systematic identification of dominant thematic patterns and sentiment orientations that function as proxy indicators of environmental risk, governance effectiveness, and public trust. Similar indicator-oriented approaches have been recommended in recent environmental assessment literature to complement biophysical measurements with socially derived monitoring indicators (Wu et al., 2021 ; Zhang et al., 2024 ). The empirical application of this monitoring framework was conducted using data from a medium-sized urban context in Iran, where persistent MSW management challenges coexist with active local digital media engagement. Such contexts provide a suitable setting for evaluating media-derived indicators, particularly where conventional monitoring data are incomplete or insufficiently responsive. Characteristics of the study area and its institutional context are detailed in the following section. Study Area and Demographic Context The analytical framework was empirically applied within a medium-sized urban context, a settlement type increasingly recognized as facing distinct MSW governance and monitoring challenges. The case study was conducted in Saveh, a medium-sized city located in Markazi Province, central Iran, situated at an elevation of approximately 1,008 meters above sea level. According to the 2016 national census, Saveh has a population of 220,762 residents, with a relatively balanced gender distribution and a high literacy rate among residents aged ≥ 6 years, and a predominantly urban settlement pattern. The age structure is dominated by the working-age population (15–64 years), a characteristic that underpins active social participation and institutional engagement in MSW management. These demographic characteristics are significant for interpreting media-derived monitoring indicators in several respects. High urbanization, literacy levels, and a predominantly working-age population increase the likelihood that local digital media platforms serve as active spaces for public reporting and feedback on municipal services. Additionally, this demographic profile suggests frequent interactions with waste collection systems and heightened sensitivity to service reliability and environmental conditions. As a result, these factors position local media discourse as a valuable proxy for public observation and response in MSW governance. For a more detailed understanding, a summary of key demographic indicators for Saveh and the surrounding county is provided in Table 1 , which contextualizes the interpretation of thematic and sentiment-based monitoring indicators derived from media analysis. Table 1 Demographic profile of the study area (city and county, 2016 census) Indicator Saveh City Saveh County Population 220,762 283,538 Households 67,230 – Gender (M/F) 112,742 / 108,020 – Age groups – 0–14: 70,584; 15–64: 198,022; 65+: 14,932 Literacy (≥ 6 years) – Literate: 225,308; Illiterate: 28,309 Urban vs. Rural Entirely urban Urban: 233,377; Rural: 50,159 Elevation (m) ~ 1,008 – Data Collection Textual data were systematically collected from three major social media platforms—Telegram, Eitaa, and Bale—and local online news platforms updates published between spring 2022 and spring 2025. These platforms were selected due to their widespread usage within the Saveh community, with Telegram and Eitaa serving as primary channels for public discourse. Local news platforms were also included due to their role in disseminating real-time information related to municipal services, local governance, and community initiatives, which are critical for understanding public perceptions of MSW management. To ensure the data reflected sustained and representative public discourse, only publicly accessible channels and groups with a minimum of 500 members were included, provided they demonstrated consistent posting activity within the three months. Channels and groups with no posts or comments for over the three months were considered inactive and excluded from the dataset to ensure that only active, representative discourse was captured. Textual data were systematically collected from publicly accessible local digital media platforms, including Telegram, Eitaa, Bale, and city-level online news outlets (refer to digital news platforms that primarily cover local affairs, governance, services, and social issues within a specific city). These platforms were selected because they function as primary venues for routine public reporting, commentary, and discussion related to municipal services and local governance. In the context of MSW management, such platforms constitute continuous, publicly observable data streams that capture citizen observations of service performance, environmental conditions, and institutional responsiveness. To ensure that the dataset reflected sustained and socially relevant discourse, inclusion criteria were applied at the channel and group level. Only publicly accessible channels and groups with a minimum of 500 registered members were included, a threshold adopted to reduce idiosyncratic or highly localized narratives and to enhance the stability of aggregated monitoring indicators. In addition, eligible sources were required to demonstrate consistent posting activity during the month preceding data collection, ensuring temporal relevance and continuity of discourse. Private channels and sources with limited public visibility were excluded. Channels and groups exhibiting prolonged inactivity—defined as an absence of posts or user interactions over a three-month period—were also excluded to avoid incorporating outdated or episodic content. These selection criteria were designed to maximize the reliability, representativeness, and monitoring relevance of the media corpus used for subsequent analysis. Data Extraction and Preprocessing In the defined study period, the research team conducted an initial manual screening of local digital media sources to identify and retain content explicitly related to MSWmanagement. This screening step was implemented to ensure conceptual relevance of the analytical corpus and to reduce thematic noise prior to automated processing. All eligible texts were subsequently compiled into a single consolidated corpus, preserving their original wording and chronological order to maintain the integrity of temporal discourse patterns. The consolidated corpus was then transferred to the Google Colab environment, which served as the unified computational workspace for all subsequent preprocessing and analytical procedures. Within this environment, data handling, text transformation, and modeling were conducted exclusively using Python-based natural language processing tools. The use of a single cloud-based computational platform ensured methodological consistency, reproducibility of analytical workflows, and transparent documentation of all preprocessing and modeling steps, which is essential for monitoring-oriented analyses based on large-scale textual data. Given the linguistic and structural characteristics of Persian-language text, preprocessing procedures were specifically tailored to minimize noise and reduce bias in subsequent thematic and sentiment-based indicator extraction. Persian-specific natural language processing tools, particularly the Hazm library, were employed to address challenges related to script variation, orthographic inconsistency, and morphological richness, which can otherwise distort both frequency-based and embedding-based analyses (Sobhani, 2017 ). Preprocessing operations included script normalization, removal of diacritics and non-textual symbols, correction of common orthographic inconsistencies, tokenization, and morphological normalization through stemming and lemmatization. These procedures collectively transformed raw media content into a structured and analytically stable corpus suitable for topic modeling and sentiment analysis, ensuring that extracted monitoring signals reflected substantive patterns in public discourse rather than artifacts of language or platform-specific formatting (Chai, 2023 ). Analytical Methods All analytical procedures were conducted within the same computational environment. To analyze the large-scale textual data collected from local media platforms, a combination of topic modeling and sentiment analysis was employed. These methods were selected for their ability to extract both thematic and emotional dimensions of public discourse, which are central to understanding governance performance and public engagement in MSW management. Topic Modeling Topic modeling was performed using Latent Dirichlet Allocation (LDA), a probabilistic technique designed to identify latent thematic structures within large textual corpora(Blei et al., 2003 ). LDA assumes that each document in the dataset is a mixture of topics, with each topic being represented by a distribution over words. The analysis identified dominant themes related to MSW management and public perception, such as waste disposal practices, recycling infrastructure, and service reliability. These themes served as proxy indicators of the public's awareness and concerns regarding MSW governance. Additionally, BERTopic was used as a complementary technique to enhance the robustness of thematic extraction through semantic clustering via transformer-based embeddings, allowing for a more nuanced understanding of the data (Blei et al., 2003 ; Medvecki et al., 2023 ). LDA was employed to ensure interpretability and compatibility with indicator construction, while BERTopic was used as a robustness check to assess semantic consistency across embedding-based clustering. Sentiment Analysis Sentiment analysis was applied to determine the emotional tone of the media content, using both a supervised machine learning classifier and a Persian sentiment lexicon to classify content into categories of positive, negative, or neutral sentiment. This method also identified more granular emotional responses, including anger, concern, hope, and satisfaction, which were indicative of the public's emotional engagement with MSW-related issues (Bing, 2012 ). The sentiment analysis framework was validated through manual coding and comparison with human annotations to ensure the accuracy and relevance of sentiment classification. Monitoring and Indicator Generation The extracted themes and sentiment signals were then interpreted as monitoring indicators, reflecting key dimensions of governance performance, environmental risk, and public trust. These indicators were contextualized within the framework of environmental monitoring by linking them to established measures of MSW service quality, transparency, and institutional responsiveness (Wu et al., 2021 ; Zolnoori et al., 2019 ). By combining both topic modeling and sentiment analysis, this dual approach enabled a comprehensive understanding of the public's evolving perceptions of MSW governance, filling critical gaps often left by traditional technical monitoring systems. Mathematical Conceptual Framework The mathematical expressions are provided as a conceptual formalization rather than as exact computational procedures. To operationalize local digital media discourse as a complementary monitoring layer in MSW governance, a semi-formal conceptual–mathematical framework was used to translate unstructured textual data into perception-based monitoring indicators, consistent with recent advances in environmental monitoring and indicator construction (Scheinberg et al., 2010 ; Wu et al., 2021 ; Zolnoori et al., 2019 ). Let X=[x 1 ,x 2 ,…,x n ] denote the corpus of n publicly available textual documents collected from local digital media platforms, where each document corresponds to a post, comment, or news item related to MSW management. Following standard natural language processing procedures, each document xi is transformed into a structured feature representation d = f(x i ), where f(x i ) denotes text normalization, tokenization, and vectorization steps commonly adopted in text-mining-based environmental assessments(Chai, 2023 ; Palomino & Aider, 2022 ). Latent Dirichlet Allocation (LDA) is employed to identify latent thematic structures within the corpus(Blei et al., 2003 ). Under this framework, each document d is represented as a probabilistic mixture of k latent topics, where \(\:{\theta\:}_{d,k}\:\) denotes the proportion of topic k in document d. Topic modeling has been widely applied to environmental governance and monitoring contexts to extract issue salience from large-scale textual data (Wu et al., 2021 ; Zolnoori et al., 2019 ). The overall prominence of topic k across the corpus is calculated as: $$\:{W}_{k}=\:\frac{1}{D}\sum\:_{d=1}^{D}{\theta\:}_{d,k}$$ where D denotes the total number of documents. The resulting value W k represents the thematic weight of topic k and functions as a topic-based monitoring indicator reflecting the relative salience of specific MSW-related governance and environmental issues in local media discourse. Each document is further assigned a sentiment score S d using a hybrid sentiment analysis approach combining supervised machine-learning classification and lexicon-based methods (Liu, 2012; Zolnoori et al., 2019 ). Sentiment scores are normalized to the interval [-1, + 1], where negative values indicate unfavorable sentiment and positive values indicate favorable sentiment toward MSW-related conditions or services. Topic-specific emotional orientation is then derived using a weighted formulation: $$\:{S}_{k}=\frac{\sum\:_{d=1}^{D}{s}_{d}\times\:{\theta\:}_{d,k}}{{\sum\:}_{d=1}^{D}{\theta\:}_{d,k}}$$ The final sentiment-adjusted monitoring indicator integrates topic prominence and emotional orientation: $$\:{I}_{k}^{sentiment}={W}_{k}\times\:{S}_{k}$$ Here, W k reflects the relative salience of MSW governance topics in local media, while I k sentiment captures the corresponding public sentiment dimension. These perception-based indicators complement conventional MSW technical metrics by incorporating qualitative governance and trust signals, as supported in prior environmental monitoring studies (Scheinberg et al., 2010 ; Wu et al., 2021 ). An overview of the analytical framework used to translate local media discourse into monitoring-relevant indicators is provided in Fig. 1 . Results and Discussion Media-Derived Thematic Indicators of MSW Governance The integrated analysis of local digital media (combining topic modeling with sentiment analysis), the study translates unstructured media narratives into measurable signals related to environmental risk, service reliability, and institutional performance. These results demonstrate how local media content can complement conventional MSW monitoring systems by capturing dimensions that are otherwise difficult to observe through technical indicators alone. The lexical analysis revealed that discourse was strongly centered around terms associated with municipal solid waste and local governance. The most frequently occurring words included waste, city, and municipality, reflecting a clear linkage between public service concerns and local identity. Table 2 summarizes the ten most prevalent terms extracted from the corpus, highlighting core thematic elements emphasized in local media discussions. Table 2 Ten most frequent keywords in local media discourse on municipal solid waste (2022–2025) Rank Word (Persian → English) Frequency 1 پسماند (Waste) 257 2 شهر (City) 202 3 زباله (Garbage) 181 4 شهرداری (Municipality) 178 5 سازمان (Organization) 136 6 مدیریت (Management) 126 7 شهری (Urban) 97 8 زیست (Life/Eco) 71 9 محیط (Environment) 65 10 شهروندان (Citizens) 64 Topic modeling revealed five dominant media-derived themes that structured MSW-related discourse across the study period. These themes, summarized in Table 3 , were subsequently translated into monitoring-relevant indicators to inform the assessment of MSW governance. Collectively, the indicators captured a substantial share of the topic probability mass, suggesting that they reflect the main dimensions through which MSW governance is publicly observed and discussed. Table 3 outlines the thematic structure and corresponding indicators, whereas Fig. 2 offers an additional visual perspective by visually depicting the relative prominence of frequently used waste-related terms that support and contextualize these themes within local media discourse. The first and most persistent indicator relates to unsanitary waste disposal practices and leachate leakage. This theme exhibited the highest thematic prominence across the analyzed corpus and was characterized by repeated references to soil and water contamination, unpleasant odors, and perceived public health risks. Its sustained prominence over time suggests that environmental exposure associated with waste disposal represents a stable and unresolved monitoring signal. From an environmental monitoring perspective, this indicator functions as a qualitative proxy for contamination risk and deficiencies in disposal-site management. The second indicator captures perceived limitations in recycling and composting infrastructure. This theme ranked among the most recurrent topics and was dominated by references to implementation delays, operational interruptions, and uncertainty regarding long-term system viability. As a monitoring signal, it reflects public assessments of institutional capacity and system resilience, highlighting gaps between policy commitments and operational performance. Table 3 Media-derived themes and their relevance for environmental monitoring of MSW governance Media-Derived Theme Description of Dominant Media Narratives Monitoring Relevance Indicator Dimension Unsanitary waste disposal and leachate impacts Reports on leachate leakage, soil and groundwater contamination, unpleasant odors, and health concerns Proxy indicator of environmental contamination risk Environmental risk Gaps in recycling and composting infrastructure Delays, operational interruptions, and uncertainty regarding recycling and composting facilities Indicator of system capacity and operational adequacy Service performance Contractor performance deficiencies Irregular collection schedules, uneven spatial service coverage, and weak responsiveness to complaints Signal of governance effectiveness and accountability Institutional performance Informal waste picking activities Media narratives linking waste picking to poverty, marginalization, and occupational health risks Indicator of social vulnerability and public health risk Public health Public dissatisfaction with municipal services Complaints, distrust, and calls for accountability and transparency Proxy for institutional legitimacy and public trust Governance & public trust The third indicator reflects dissatisfaction with private waste collection contractors. This theme was characterized by frequent references to irregular collection schedules, uneven spatial service coverage, and limited responsiveness to complaints, particularly in peripheral urban areas. The consistency of this discourse indicates that service reliability constitutes a key dimension through which governance performance is publicly evaluated. In monitoring terms, contractor-related narratives serve as indirect indicators of operational efficiency and accountability. The fourth indicator centers on informal waste picking (zobale-gardi), which emerged as a recurrent and visible topic across platforms. Media narratives frequently associated waste picking with poverty, social marginalization, and heightened health risks. The prominence of this theme positions it as a composite indicator capturing both social vulnerability and regulatory gaps within the MSW governance framework. The fifth thematic indicator reflects generalized public dissatisfaction and institutional mistrust. This theme aggregated complaints, skepticism toward announced reforms, and explicit demands for accountability. Although less directly linked to physical waste flows, this indicator captures a critical governance dimension—public trust—that remains largely absent from conventional MSW monitoring systems. The thematic indicators identified in this study are broadly consistent with findings from previous research applying media-based and text-analytic approaches to environmental governance and waste management. Studies conducted in rapidly urbanizing contexts have similarly reported the prominence of service reliability, waste infrastructure performance, and public dissatisfaction as dominant themes in local media discourse (Jiang et al., 2021 ; Yandri et al., 2023 ). Contractor performance and informal waste practices have also been highlighted as salient public-facing governance concerns in prior work (Wu et al., 2021 ). However, the present study advances this literature by explicitly operationalizing these recurrent discourse themes as monitoring-relevant indicators, rather than treating them solely as descriptive patterns. By linking thematic prominence to governance performance dimensions, the analysis provides a structured pathway for integrating media-derived signals into environmental monitoring and assessment frameworks. Sentiment-Based Indicators and Emotional Dynamics Sentiment analysis added a quantitative interpretive layer to the thematic indicators by characterizing the emotional orientation of media discourse on MSW management (Table 3 ). Overall, negative sentiment predominated, with anger representing 32% of the analyzed content and concern accounting for 23%. These negative emotional expressions were primarily associated with narratives describing service interruptions, environmental exposure, and perceived institutional inaction. Positive sentiment, while less prevalent, was consistently linked to reports of tangible municipal interventions. Expressions of hope (18%) and satisfaction (12%) corresponded mainly to coverage of infrastructure-related actions, including the reopening of composting facilities, the deployment of mechanized underground waste containers, and the implementation of public education initiatives. Neutral sentiment constituted approximately 15% of the corpus and was largely confined to factual or informational reporting lacking explicit evaluative judgment. Table 3 Distribution of sentiment categories in local media discourse on MSW management Sentiment Category Percentage (%) Dominant Associated Themes Anger 32 Service disruptions, contractor failures, environmental exposure Concern 23 Leachate contamination, public health risks Hope 18 Composting initiatives, infrastructure improvements Satisfaction 12 Visible municipal interventions Neutral 15 Informational and descriptive reports Polarity scores derived from machine-learning classification further supported this pattern. Mean sentiment values were + 0.74 for the training dataset and + 0.68 for the test dataset, indicating that despite frequent criticism, the overall tone of the discourse remained moderately positive. Despite the dominance of negative emotions, polarity scores remained positive due to the co-occurrence of criticism with solution-oriented and improvement-related narratives. This suggests that negative evaluations were often accompanied by expressions of optimism or approval when tangible improvements were observed. Overall, the emotional profile reflects sustained public engagement rather than disengagement or hostility. From an environmental monitoring perspective, the use of media-derived indicators aligns with recent efforts to incorporate socially derived data into environmental assessment frameworks. Previous studies have demonstrated the value of indirect indicators, such as citizen reports and media narratives, in identifying governance gaps and emerging environmental risks (Zhang et al., 2024 ; Zolnoori et al., 2019 ). Compared to earlier applications that primarily emphasized sentiment or thematic prevalence, the present study advances the field by linking thematic prominence and emotional orientation to specific dimensions of MSW system performance, including environmental exposure, service reliability, and public trust. The identified indicators provide early-warning signals of environmental exposure (unsanitary disposal and leachate), operational stress (service irregularities and infrastructure gaps), social vulnerability (waste picking), and governance performance (public trust and accountability). In practice, the timing and spatial specificity of media-derived signals depend on posting behavior and platform usage patterns, which varied across neighborhoods during the study period. When interpreted within environmental monitoring frameworks, this indicator suggests, integrating media-based indicators alongside established technical metrics can enhance the sensitivity, contextual awareness, and responsiveness of MSW monitoring systems. Such integration aligns with broader shifts in environmental governance toward participatory monitoring, transparency, and adaptive management, particularly in rapidly urbanizing settings where formal data collection may be delayed or incomplete. The thematic and sentiment-based indicators demonstrate that local digital media discourse may function as a complementary, perception-based monitoring signal. Unlike conventional monitoring systems that rely on periodic technical measurements, media-derived indicators reflect continuous public observation of environmental conditions, service performance, and institutional responsiveness. The identified indicators provide early-warning signals of environmental exposure (unsanitary disposal and leachate), operational stress (service irregularities and infrastructure gaps), social vulnerability (informal waste picking), and governance performance (public trust and accountability). Significantly, these signals emerge in near real time and capture dimensions of system performance that are directly visible to affected communities but often remain underrepresented in formal monitoring frameworks. Integrating media-based indicators alongside established technical metrics can therefore enhance the sensitivity, contextual awareness, and responsiveness of MSW monitoring systems. Such integration aligns with broader shifts in environmental governance toward participatory monitoring, transparency, and adaptive management, particularly in urban contexts where formal data collection may be delayed, fragmented, or incomplete. By translating unstructured media narratives into thematic and sentiment-based indicators, the analysis extends conventional MSW monitoring beyond technical and infrastructural metrics to include governance performance, public trust, and experiential exposure to environmental risk. The results show that recurrent media themes—such as unsanitary waste disposal, infrastructure gaps, contractor performance deficiencies, informal waste picking, and institutional mistrust—function as stable, monitoring-relevant signals that reflect public-facing dimensions of MSW system performance. When interpreted through an environmental monitoring lens, these themes operate as qualitative proxies for contamination risk, service reliability, institutional accountability, and social vulnerability. Unlike conventional indicators derived from periodic measurements, media-based signals emerge continuously and are grounded in lived experience, allowing emerging issues to be detected earlier and at finer spatial and temporal scales. Sentiment-based indicators further enhance the monitoring value of media discourse by capturing the emotional orientation associated with observed conditions and governance responses. Although negative emotions such as anger and concern were prevalent, the simultaneous presence of hope and satisfaction indicates that public criticism is often conditional rather than oppositional. From an assessment perspective, this emotional configuration reflects sustained civic engagement and responsiveness to observable improvements, rather than systemic disengagement or distrust. Such sentiment dynamics provide additional interpretive depth that is typically absent from technical monitoring datasets. While the identified themes function as monitoring-relevant signals, their interpretation depends on the activity level and representativeness of local media platforms. In less active media environments, such indicators may underestimate governance stress. From an environmental governance standpoint, integrating media-derived indicators into MSW monitoring frameworks can enhance transparency, adaptive management, and participatory assessment. The Saveh case illustrates how media analytics can support early warning, contextual interpretation of technical data, and alignment of municipal interventions with public expectations. More broadly, this approach contributes to ongoing shifts in environmental monitoring and assessment toward hybrid systems that combine biophysical measurements with socially derived signals, particularly in rapidly urbanizing contexts where formal data collection may be delayed or incomplete. This study demonstrates the value of computational analysis of local media content for urban environmental monitoring and assessment. By revealing how environmental risks, service deficiencies, and institutional responses are perceived and communicated, media-based analysis extends conventional monitoring approaches. The results suggest that comprehensive assessment of MSW performance should integrate technical indicators with social signals embedded in public discourse, particularly in rapidly urbanizing contexts. 5. 3 Interpretation of Findings in the Context of Environmental Monitoring The results presented above extend beyond descriptive patterns of media discourse and can be interpreted as monitoring-relevant signals within an environmental governance framework. Unlike conventional MSW monitoring systems, which primarily rely on technical and operational metrics, the indicators derived in this study reflect how environmental risks, service performance, and institutional responsiveness are perceived and evaluated by affected communities. From an environmental monitoring perspective, the persistence of themes related to unsanitary disposal practices and leachate leakage suggests that public discourse may function as an informal early-warning system. Recurrent references to odors, contamination, and health concerns indicate perceived environmental exposure that may precede or escape detection through routine technical inspections. Similar interpretive roles of citizen-generated or media-based signals have been discussed in prior monitoring-oriented studies (Zhang et al., 2024 ; Zolnoori et al., 2019 ). In addition, themes related to service reliability and contractor performance highlight dimensions of MSW systems that are difficult to capture through infrastructure-focused indicators alone. While collection coverage or fleet capacity may appear adequate in official reports, media narratives reveal how irregularity, spatial inequality, and responsiveness shape public evaluation of system effectiveness. In this sense, media-derived indicators complement technical monitoring by capturing performance as experienced rather than as designed. The presence of waste picking as a dominant and persistent theme further illustrates the added value of discourse-based monitoring. Informal recovery activities simultaneously reflect economic vulnerability, regulatory gaps, and occupational health risks. Their visibility in local media suggests that such practices constitute a salient governance signal, even when they remain weakly represented in formal waste statistics. Finally, expressions of dissatisfaction and institutional mistrust represent a governance dimension that is largely absent from conventional MSW monitoring frameworks. Although trust cannot be directly measured through physical indicators, its recurring articulation in public discourse provides insight into perceived legitimacy, accountability, and transparency. Interpreted as a monitoring signal, institutional mistrust may indicate declining system credibility and reduced public cooperation, both of which have implications for long-term system sustainability (Jiang et al., 2021 ; Wu et al., 2021 ). Governance and Policy Implications The findings demonstrate the dual governance role of local digital media within MSW systems. Media platforms function both as informal watchdogs—exposing service deficiencies, environmental risks, and governance failures—and as facilitators by disseminating information on corrective actions and infrastructure improvements. This balance between critical and constructive narratives appears more effective in sustaining public engagement and institutional accountability than exclusively negative framing (Bennett, 2001 ; Bruns et al., 2016 ; Fung, 2015 ). From an assessment standpoint, the Saveh case reflects a shift toward participatory evaluation models in which MSW performance is assessed not only through technical indicators but also through responsiveness, transparency, and public perception. This approach aligns with hybrid environmental monitoring frameworks that integrate expert-driven measurements with citizen-generated and perception-based data, thereby enhancing contextual sensitivity and interpretive capacity (Conrad & Hilchey, 2011 ; Wehn & Evers, 2015 ). Thematic analysis identified governance-relevant dimensions of MSW performance related to environmental exposure, infrastructure capacity, service reliability, social vulnerability, and public trust. Perception-based narratives on unsanitary disposal and leachate leakage function as early-warning signals of environmental and public health risks, particularly in contexts with limited formal monitoring (Hadjimitsis et al., 2010 ). Discourse on recycling infrastructure and contractor performance highlights structural and contractual weaknesses often underrepresented in conventional MSW metrics (Guerrero et al., 2013 ; Wilson et al., 2015 ), while attention to informal waste picking underscores links between MSW governance, inequality, and environmental justice (Gutberlet et al., 2017 ). Persistent expressions of public mistrust further signal governance stress and misalignment between institutional performance and societal expectations. Despite predominantly critical narratives, constructive reporting on infrastructure upgrades and community education initiatives indicates that local media also support adaptive governance by amplifying successful interventions and encouraging cooperative public behavior (Emerson & Nabatchi, 2015 ). Table 5 highlights the complementary role of media-derived indicators in municipal solid waste monitoring. While conventional indicators primarily capture technical and infrastructural performance, media-based indicators provide near real-time insights into governance effectiveness, public trust, and perceived environmental risks. By reflecting citizen experiences and institutional responsiveness, media discourse enhances early-warning capacity and contextual interpretation of formal monitoring data. Integrating media-derived indicators with conventional metrics therefore supports a more adaptive and comprehensive environmental monitoring framework. Table 5 Advantages of media-based indicators compared to conventional MSW monitoring Monitoring Aspect Conventional MSW Indicators Media-Derived Indicators Temporal resolution Periodic Near real-time Governance performance Limited Explicit Public trust & perception Rarely captured Directly observable Early warning capacity Low High Social vulnerability Often omitted Clearly reflected Conclusion This work demonstrates that local digital media may function as a complementary, perception-based monitoring layer within MSW systems. It does not aim to replace technical MSW monitoring systems. Rather, it proposes media-derived indicators as supplementary signals that may enhance situational awareness, especially where conventional data are delayed or incomplete. By systematically translating unstructured media discourse into thematic and sentiment-based indicators, the analysis captures qualitative signals related to environmental risk, service reliability, institutional performance, and public trust—dimensions that are often insufficiently represented in conventional, technically oriented monitoring frameworks. From an environmental monitoring and assessment standpoint, media-derived indicators provide early-warning signals and contextual information that enhance both the sensitivity and interpretability of MSW performance assessments. Integrating such indicators alongside established technical metrics can support more adaptive, transparent, and participatory governance processes, particularly in rapidly urbanizing urban contexts where formal monitoring data may be delayed or incomplete. Although the findings are derived from a single urban case, the proposed analytical framework is transferable to other cities with active local media ecosystems. Future research should extend this approach through comparative and longitudinal analyses, as well as by integrating media-based indicators with conventional environmental and operational datasets, to further assess their contribution to robust and responsive MSW monitoring and assessment systems. Declarations Ethics approval and consent to participate This study was conducted as part of a research project approved by the Ethics Committee of Saveh University of Medical Sciences (Ethics code: IR.SAVEHUMS.REC.1403.027). All analyzed data were obtained from publicly accessible media sources. No private, sensitive, or personally identifiable information was collected or analyzed. The study was performed in accordance with institutional and national ethical standards for research involving publicly available digital content. Consent for publication Not applicable. Conflicts of interest The authors declare that they have no competing interests. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Author Contribution Reza Nemati: Supervision, Project administration, Funding acquisition, Writing – review & editing.AliReza Bagheri Resaei: Data curation, Formal analysis, Writing – review & editing.Narges Hakimi: Conceptualization, Methodology, Investigation, Writing – original draft.All authors have read and approved the final manuscript. Acknowledgments The authors gratefully acknowledge the support of Saveh University of Medical Sciences. Data Availability Datasets generated and analyzed during the current study are derived from publicly available local media sources. The processed data supporting the findings of this study are available from the corresponding author upon reasonable request. References Bennett, S. E. (2001). 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05:22:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":23323,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of the most frequent waste-related keywords identified in local social media content from Saveh during the study period (2022–2025).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8525042/v1/4f3de6c89d3a5a2d8b453030.png"},{"id":100377001,"identity":"eb9a8d20-1a4a-4893-9e45-9c6511904df0","added_by":"auto","created_at":"2026-01-16 08:46:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1609962,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8525042/v1/8cd86481-ce62-4850-bf09-0f22fa001bce.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Local Media–Derived Indicators for Monitoring Municipal Solid Waste Governance: A Text-Mining Assessment","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRapid urbanization, coupled with escalating environmental pressures, has intensified the complexity of municipal solid waste (MSW) management worldwide, with consequences extending beyond environmental degradation to public health risks and the reliability of urban service provision. Inadequate waste collection, unsanitary disposal practices, and uncontrolled activities such as open burning contribute to air, soil, and water contamination, thereby exacerbating infectious, respiratory, and cardiovascular health outcomes (Ferronato \u0026amp; Torretta, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Ncube et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These challenges underscore the need not only for improved technical interventions but also for effective monitoring approaches capable of capturing system performance and emerging risks within urban waste governance\u003c/p\u003e \u003cp\u003eCollective participation plays a critical role in municipal solid waste governance by shaping transparency, accountability, and public confidence in decision-making processes. Beyond its normative importance, participation also generates observable signals through public communication, feedback, and collective responses to waste management practices. The engagement of community members and institutional actors therefore constitutes not only a governance objective but also a source of information through which the performance and legitimacy of MSW systems can be assessed. (Hinds \u0026amp; Sparks, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Huang et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Youngquist et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Despite advances in technical monitoring of municipal solid waste systems, existing assessment approaches often remain narrowly focused on operational and infrastructural indicators, such as collection coverage, disposal capacity, and treatment efficiency (Cervantes et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sasahara et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Wilson et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). While these metrics are essential, they provide limited insight into governance performance, institutional responsiveness, and public-facing dimensions of waste management (Rodić \u0026amp; Wilson, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). As a result, early signals of service failure, declining trust, or emerging environmental risks may remain undetected until they manifest as systemic problems (Scheinberg et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). This limitation highlights the need for complementary monitoring approaches capable of capturing qualitative, real-time information related to governance processes and public experience (Rodić \u0026amp; Wilson, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEffective municipal solid waste management is increasingly recognized as a governance challenge rather than a purely technical one. Although investments in collection systems, treatment facilities, and disposal technologies remain indispensable, their long-term effectiveness is closely tied to public engagement, behavioral responses, and institutional accountability (Ferronato \u0026amp; Torretta, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Empirical evidence suggests that even technically advanced waste systems may fail to deliver sustained environmental and health benefits when community involvement is fragmented or weak (Kuang \u0026amp; Lin, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These observations have prompted a growing emphasis on governance frameworks that incorporate social, behavioral, and communicative processes\u0026mdash;dimensions that shape how waste management policies are interpreted, contested, and enacted in practice.\u003c/p\u003e \u003cp\u003eCommunication-oriented interventions, including awareness campaigns, environmental education, and participatory feedback mechanisms, have been associated with measurable changes in waste-related behaviors such as source separation, recycling, and composting (Konstantinidou et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Beyond their instrumental role in promoting compliance, these interventions generate continuous streams of public communication through which attitudes, expectations, and responses to municipal waste services are expressed. When embedded within broader governance frameworks, such communicative processes contribute to the formation and maintenance of public trust and civic responsibility over time (Kuang \u0026amp; Lin, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), while simultaneously offering observable signals relevant to the assessment of MSW governance performance.\u003c/p\u003e \u003cp\u003eIn many rapidly urbanizing contexts, municipal solid waste management continues to be shaped by structural and operational constraints, including limitations in treatment capacity, service coverage, and regulatory enforcement (Zhang et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Under such conditions, public behavior and collective responses play a decisive role in shaping waste generation, separation, and disposal practices(Chen et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sasahara et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), thereby amplifying the relevance of communication processes within waste governance(Pan et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The expansion of digital platforms and locally oriented online media has transformed urban information environments, enabling continuous, publicly accessible exchanges through which waste-related experiences, concerns, and evaluations are expressed (Khan et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These local media spaces increasingly function as arenas where governance performance is observed, discussed, and implicitly assessed (Khan et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInternational evidence from diverse contexts\u0026mdash;including China, Indonesia, and Australia\u0026mdash;demonstrates that local and community-based media can play a meaningful role in shaping public participation in recycling initiatives, food waste reduction, and environmentally responsible behaviors (Jiang et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Shittu et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Yandri et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Beyond their communicative function, these platforms increasingly generate real-time, perception-based information that reflects public responses to municipal services and governance practices. Such characteristics position local media as potentially valuable, yet underutilized, sources of indirect monitoring data for MSW management.\u003c/p\u003e \u003cp\u003eIn practical monitoring terms, these findings indicate, discourse within local digital media may complement conventional technical indicators by capturing qualitative signals related to environmental risk, service performance, institutional accountability, and public trust. Analyzing these narratives offers a means to identify emerging governance challenges and societal concerns that are often overlooked by infrastructure-focused assessments. As such, media-based analysis may enhance the responsiveness and contextual sensitivity of environmental governance frameworks (Ghermandi et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eText-mining approaches provide a systematic and scalable means of extracting patterns from large volumes of unstructured media content. By enabling the quantitative identification of dominant themes and sentiment orientations, these methods facilitate the translation of narrative discourse into structured, monitoring-relevant information (Bing, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; DiMaggio et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Grimmer \u0026amp; Stewart, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In contexts where large-scale surveys or participatory assessments are limited by logistical or financial constraints, computational analysis of publicly accessible digital media offers a reproducible and ethically viable alternative for inferring public perceptions and engagement (Zolnoori et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite growing international interest in media-informed environmental governance, research on MSW management in Iran has largely emphasized technical, infrastructural, and operational dimensions. In medium-sized Iranian cities such as Saveh, municipal solid waste services are frequently evaluated by citizens through local digital media rather than formal reporting channels. The communicative and monitoring potential of local media\u0026mdash;particularly their capacity to reflect citizen participation, dissatisfaction, and trust in municipal waste governance\u0026mdash;remains insufficiently examined. This gap is especially consequential in medium-sized urban settings, where persistent MSW challenges coexist with active local digital media ecosystems. In such contexts, local media may simultaneously function as watchdogs that highlight governance deficiencies and as facilitators that promote constructive engagement and pro-environmental behavior (Wu et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, local media are conceptualized as publicly accessible digital news outlets and community-oriented social media channels operating at the city scale. Using a descriptive\u0026ndash;analytical text-mining framework, the study examines how discourse published across local digital platforms between 2022 and 2025 reflects public participation and perceived governance performance in MSW management. By integrating computational text analysis with an environmental monitoring and public health perspective, the research contributes empirical evidence on the utility of media-based indicators for strengthening transparency, participation, and adaptive governance in municipal solid waste systems.\u003c/p\u003e \u003cp\u003eTo ensure an explicitly analytical and monitoring-oriented focus, this study addresses the following research questions:\u003c/p\u003e \u003cp\u003eRQ1. Can local digital media discourse be operationalized into reproducible indicators relevant to municipal solid waste (MSW) monitoring?\u003c/p\u003e \u003cp\u003eRQ2. Which MSW performance dimensions\u0026mdash;environmental risk, service reliability, or governance performance\u0026mdash;are most prominently reflected in media-derived indicators?\u003c/p\u003e \u003cp\u003eRQ3. Do temporal variations in media-derived indicators exhibit characteristics consistent with potential early-warning signals for MSW governance stress?\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eThis study was designed within the context of an environmental monitoring and assessment framework to address recognized limitations of conventional MSW monitoring systems. In this study, monitoring is operationally defined as the systematic detection of recurrent, publicly observable signals that indicate deviations, stress, or risk within MSW systems, prior to their formal registration in technical or regulatory datasets. Traditional MSW monitoring largely relies on technical and operational indicators, which often fail to capture governance performance, service reliability, and public response in a timely manner (Scheinberg et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Wilson et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). To complement these limitations, the present study conceptualizes local digital media discourse as a perception-based monitoring layer capable of generating qualitative indicators relevant to MSW governance. A descriptive\u0026ndash;analytical text-mining design was adopted to systematically extract, structure, and interpret monitoring indicators embedded in local media content (Rivera et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Zolnoori et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Within this framework, media discourse is treated not merely as communication output, but as an observational data stream reflecting public encounters with environmental conditions, service disruptions, and institutional responsiveness.\u003c/p\u003e \u003cp\u003eThe methodological framework comprised four sequential and interrelated stages: data collection, data extraction, text preprocessing, and analytical modeling. This structure enabled the systematic identification of dominant thematic patterns and sentiment orientations that function as proxy indicators of environmental risk, governance effectiveness, and public trust. Similar indicator-oriented approaches have been recommended in recent environmental assessment literature to complement biophysical measurements with socially derived monitoring indicators (Wu et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe empirical application of this monitoring framework was conducted using data from a medium-sized urban context in Iran, where persistent MSW management challenges coexist with active local digital media engagement. Such contexts provide a suitable setting for evaluating media-derived indicators, particularly where conventional monitoring data are incomplete or insufficiently responsive. Characteristics of the study area and its institutional context are detailed in the following section.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Area and Demographic Context\u003c/h3\u003e\n\u003cp\u003eThe analytical framework was empirically applied within a medium-sized urban context, a settlement type increasingly recognized as facing distinct MSW governance and monitoring challenges.\u003c/p\u003e \u003cp\u003eThe case study was conducted in Saveh, a medium-sized city located in Markazi Province, central Iran, situated at an elevation of approximately 1,008 meters above sea level. According to the 2016 national census, Saveh has a population of 220,762 residents, with a relatively balanced gender distribution and a high literacy rate among residents aged\u0026thinsp;\u0026ge;\u0026thinsp;6 years, and a predominantly urban settlement pattern. The age structure is dominated by the working-age population (15\u0026ndash;64 years), a characteristic that underpins active social participation and institutional engagement in MSW management.\u003c/p\u003e \u003cp\u003eThese demographic characteristics are significant for interpreting media-derived monitoring indicators in several respects. High urbanization, literacy levels, and a predominantly working-age population increase the likelihood that local digital media platforms serve as active spaces for public reporting and feedback on municipal services. Additionally, this demographic profile suggests frequent interactions with waste collection systems and heightened sensitivity to service reliability and environmental conditions. As a result, these factors position local media discourse as a valuable proxy for public observation and response in MSW governance. For a more detailed understanding, a summary of key demographic indicators for Saveh and the surrounding county is provided in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, which contextualizes the interpretation of thematic and sentiment-based monitoring indicators derived from media analysis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic profile of the study area (city and county, 2016 census)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSaveh City\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSaveh County\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e220,762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e283,538\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHouseholds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67,230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (M/F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e112,742 / 108,020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u0026ndash;14: 70,584; 15\u0026ndash;64: 198,022; 65+: 14,932\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiteracy (\u0026ge;\u0026thinsp;6 years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLiterate: 225,308; Illiterate: 28,309\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban vs. Rural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEntirely urban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUrban: 233,377; Rural: 50,159\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElevation (m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e~\u0026thinsp;1,008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003eTextual data were systematically collected from three major social media platforms\u0026mdash;Telegram, Eitaa, and Bale\u0026mdash;and local online news platforms updates published between spring 2022 and spring 2025. These platforms were selected due to their widespread usage within the Saveh community, with Telegram and Eitaa serving as primary channels for public discourse. Local news platforms were also included due to their role in disseminating real-time information related to municipal services, local governance, and community initiatives, which are critical for understanding public perceptions of MSW management.\u003c/p\u003e \u003cp\u003eTo ensure the data reflected sustained and representative public discourse, only publicly accessible channels and groups with a minimum of 500 members were included, provided they demonstrated consistent posting activity within the three months. Channels and groups with no posts or comments for over the three months were considered inactive and excluded from the dataset to ensure that only active, representative discourse was captured. Textual data were systematically collected from publicly accessible local digital media platforms, including Telegram, Eitaa, Bale, and city-level online news outlets (refer to digital news platforms that primarily cover local affairs, governance, services, and social issues within a specific city). These platforms were selected because they function as primary venues for routine public reporting, commentary, and discussion related to municipal services and local governance. In the context of MSW management, such platforms constitute continuous, publicly observable data streams that capture citizen observations of service performance, environmental conditions, and institutional responsiveness.\u003c/p\u003e \u003cp\u003eTo ensure that the dataset reflected sustained and socially relevant discourse, inclusion criteria were applied at the channel and group level. Only publicly accessible channels and groups with a minimum of 500 registered members were included, a threshold adopted to reduce idiosyncratic or highly localized narratives and to enhance the stability of aggregated monitoring indicators. In addition, eligible sources were required to demonstrate consistent posting activity during the month preceding data collection, ensuring temporal relevance and continuity of discourse.\u003c/p\u003e \u003cp\u003ePrivate channels and sources with limited public visibility were excluded. Channels and groups exhibiting prolonged inactivity\u0026mdash;defined as an absence of posts or user interactions over a three-month period\u0026mdash;were also excluded to avoid incorporating outdated or episodic content. These selection criteria were designed to maximize the reliability, representativeness, and monitoring relevance of the media corpus used for subsequent analysis.\u003c/p\u003e\n\u003ch3\u003eData Extraction and Preprocessing\u003c/h3\u003e\n\u003cp\u003eIn the defined study period, the research team conducted an initial manual screening of local digital media sources to identify and retain content explicitly related to MSWmanagement. This screening step was implemented to ensure conceptual relevance of the analytical corpus and to reduce thematic noise prior to automated processing. All eligible texts were subsequently compiled into a single consolidated corpus, preserving their original wording and chronological order to maintain the integrity of temporal discourse patterns. The consolidated corpus was then transferred to the Google Colab environment, which served as the unified computational workspace for all subsequent preprocessing and analytical procedures. Within this environment, data handling, text transformation, and modeling were conducted exclusively using Python-based natural language processing tools. The use of a single cloud-based computational platform ensured methodological consistency, reproducibility of analytical workflows, and transparent documentation of all preprocessing and modeling steps, which is essential for monitoring-oriented analyses based on large-scale textual data.\u003c/p\u003e \u003cp\u003eGiven the linguistic and structural characteristics of Persian-language text, preprocessing procedures were specifically tailored to minimize noise and reduce bias in subsequent thematic and sentiment-based indicator extraction. Persian-specific natural language processing tools, particularly the Hazm library, were employed to address challenges related to script variation, orthographic inconsistency, and morphological richness, which can otherwise distort both frequency-based and embedding-based analyses (Sobhani, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Preprocessing operations included script normalization, removal of diacritics and non-textual symbols, correction of common orthographic inconsistencies, tokenization, and morphological normalization through stemming and lemmatization. These procedures collectively transformed raw media content into a structured and analytically stable corpus suitable for topic modeling and sentiment analysis, ensuring that extracted monitoring signals reflected substantive patterns in public discourse rather than artifacts of language or platform-specific formatting (Chai, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eAnalytical Methods\u003c/h3\u003e\n\u003cp\u003eAll analytical procedures were conducted within the same computational environment. To analyze the large-scale textual data collected from local media platforms, a combination of topic modeling and sentiment analysis was employed. These methods were selected for their ability to extract both thematic and emotional dimensions of public discourse, which are central to understanding governance performance and public engagement in MSW management.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eTopic Modeling\u003c/h2\u003e \u003cp\u003eTopic modeling was performed using Latent Dirichlet Allocation (LDA), a probabilistic technique designed to identify latent thematic structures within large textual corpora(Blei et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). LDA assumes that each document in the dataset is a mixture of topics, with each topic being represented by a distribution over words. The analysis identified dominant themes related to MSW management and public perception, such as waste disposal practices, recycling infrastructure, and service reliability. These themes served as proxy indicators of the public's awareness and concerns regarding MSW governance. Additionally, BERTopic was used as a complementary technique to enhance the robustness of thematic extraction through semantic clustering via transformer-based embeddings, allowing for a more nuanced understanding of the data (Blei et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Medvecki et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). LDA was employed to ensure interpretability and compatibility with indicator construction, while BERTopic was used as a robustness check to assess semantic consistency across embedding-based clustering.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSentiment Analysis\u003c/h3\u003e\n\u003cp\u003eSentiment analysis was applied to determine the emotional tone of the media content, using both a supervised machine learning classifier and a Persian sentiment lexicon to classify content into categories of positive, negative, or neutral sentiment. This method also identified more granular emotional responses, including anger, concern, hope, and satisfaction, which were indicative of the public's emotional engagement with MSW-related issues (Bing, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The sentiment analysis framework was validated through manual coding and comparison with human annotations to ensure the accuracy and relevance of sentiment classification.\u003c/p\u003e\n\u003ch3\u003eMonitoring and Indicator Generation\u003c/h3\u003e\n\u003cp\u003eThe extracted themes and sentiment signals were then interpreted as monitoring indicators, reflecting key dimensions of governance performance, environmental risk, and public trust. These indicators were contextualized within the framework of environmental monitoring by linking them to established measures of MSW service quality, transparency, and institutional responsiveness (Wu et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zolnoori et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). By combining both topic modeling and sentiment analysis, this dual approach enabled a comprehensive understanding of the public's evolving perceptions of MSW governance, filling critical gaps often left by traditional technical monitoring systems.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMathematical Conceptual Framework\u003c/h2\u003e \u003cp\u003eThe mathematical expressions are provided as a conceptual formalization rather than as exact computational procedures. To operationalize local digital media discourse as a complementary monitoring layer in MSW governance, a semi-formal conceptual\u0026ndash;mathematical framework was used to translate unstructured textual data into perception-based monitoring indicators, consistent with recent advances in environmental monitoring and indicator construction (Scheinberg et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Wu et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zolnoori et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Let X=[x\u003csub\u003e1\u003c/sub\u003e,x\u003csub\u003e2\u003c/sub\u003e,\u0026hellip;,x\u003csub\u003en\u003c/sub\u003e] denote the corpus of n publicly available textual documents collected from local digital media platforms, where each document corresponds to a post, comment, or news item related to MSW management. Following standard natural language processing procedures, each document xi is transformed into a structured feature representation d\u0026thinsp;=\u0026thinsp;f(x\u003csub\u003ei\u003c/sub\u003e), where f(x\u003csub\u003ei\u003c/sub\u003e) denotes text normalization, tokenization, and vectorization steps commonly adopted in text-mining-based environmental assessments(Chai, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Palomino \u0026amp; Aider, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Latent Dirichlet Allocation (LDA) is employed to identify latent thematic structures within the corpus(Blei et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Under this framework, each document d is represented as a probabilistic mixture of k latent topics, where \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\theta\\:}_{d,k}\\:\\)\u003c/span\u003e\u003c/span\u003edenotes the proportion of topic k in document d. Topic modeling has been widely applied to environmental governance and monitoring contexts to extract issue salience from large-scale textual data (Wu et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zolnoori et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe overall prominence of topic k across the corpus is calculated as:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:{W}_{k}=\\:\\frac{1}{D}\\sum\\:_{d=1}^{D}{\\theta\\:}_{d,k}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere D denotes the total number of documents. The resulting value W\u003csub\u003ek\u003c/sub\u003e represents the thematic weight of topic k and functions as a topic-based monitoring indicator reflecting the relative salience of specific MSW-related governance and environmental issues in local media discourse.\u003c/p\u003e \u003cp\u003eEach document is further assigned a sentiment score S\u003csub\u003ed\u003c/sub\u003e using a hybrid sentiment analysis approach combining supervised machine-learning classification and lexicon-based methods (Liu, 2012; Zolnoori et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Sentiment scores are normalized to the interval [-1, +\u0026thinsp;1], where negative values indicate unfavorable sentiment and positive values indicate favorable sentiment toward MSW-related conditions or services.\u003c/p\u003e \u003cp\u003eTopic-specific emotional orientation is then derived using a weighted formulation:\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:{S}_{k}=\\frac{\\sum\\:_{d=1}^{D}{s}_{d}\\times\\:{\\theta\\:}_{d,k}}{{\\sum\\:}_{d=1}^{D}{\\theta\\:}_{d,k}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe final sentiment-adjusted monitoring indicator integrates topic prominence and emotional orientation:\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\:{I}_{k}^{sentiment}={W}_{k}\\times\\:{S}_{k}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eHere, W\u003csub\u003ek\u003c/sub\u003e reflects the relative salience of MSW governance topics in local media, while I \u003csub\u003ek\u003c/sub\u003e\u003csup\u003esentiment\u003c/sup\u003e captures the corresponding public sentiment dimension. These perception-based indicators complement conventional MSW technical metrics by incorporating qualitative governance and trust signals, as supported in prior environmental monitoring studies (Scheinberg et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Wu et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAn overview of the analytical framework used to translate local media discourse into monitoring-relevant indicators is provided in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results and Discussion","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eMedia-Derived Thematic Indicators of MSW Governance\u003c/h2\u003e \u003cp\u003eThe integrated analysis of local digital media (combining topic modeling with sentiment analysis), the study translates unstructured media narratives into measurable signals related to environmental risk, service reliability, and institutional performance. These results demonstrate how local media content can complement conventional MSW monitoring systems by capturing dimensions that are otherwise difficult to observe through technical indicators alone.\u003c/p\u003e \u003cp\u003eThe lexical analysis revealed that discourse was strongly centered around terms associated with municipal solid waste and local governance. The most frequently occurring words included waste, city, and municipality, reflecting a clear linkage between public service concerns and local identity. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes the ten most prevalent terms extracted from the corpus, highlighting core thematic elements emphasized in local media discussions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTen most frequent keywords in local media discourse on municipal solid waste (2022\u0026ndash;2025)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWord (Persian \u0026rarr; English)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eپسماند (Waste)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e257\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eشهر (City)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e202\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eزباله (Garbage)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e181\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eشهرداری (Municipality)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e178\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eسازمان (Organization)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eمدیریت (Management)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eشهری (Urban)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eزیست (Life/Eco)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eمحیط (Environment)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eشهروندان (Citizens)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTopic modeling revealed five dominant media-derived themes that structured MSW-related discourse across the study period. These themes, summarized in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e, were subsequently translated into monitoring-relevant indicators to inform the assessment of MSW governance. Collectively, the indicators captured a substantial share of the topic probability mass, suggesting that they reflect the main dimensions through which MSW governance is publicly observed and discussed. Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e outlines the thematic structure and corresponding indicators, whereas Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e offers an additional visual perspective by visually depicting the relative prominence of frequently used waste-related terms that support and contextualize these themes within local media discourse.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe first and most persistent indicator relates to unsanitary waste disposal practices and leachate leakage. This theme exhibited the highest thematic prominence across the analyzed corpus and was characterized by repeated references to soil and water contamination, unpleasant odors, and perceived public health risks. Its sustained prominence over time suggests that environmental exposure associated with waste disposal represents a stable and unresolved monitoring signal. From an environmental monitoring perspective, this indicator functions as a qualitative proxy for contamination risk and deficiencies in disposal-site management. The second indicator captures perceived limitations in recycling and composting infrastructure. This theme ranked among the most recurrent topics and was dominated by references to implementation delays, operational interruptions, and uncertainty regarding long-term system viability. As a monitoring signal, it reflects public assessments of institutional capacity and system resilience, highlighting gaps between policy commitments and operational performance.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMedia-derived themes and their relevance for environmental monitoring of MSW governance\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedia-Derived Theme\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescription of Dominant Media Narratives\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMonitoring Relevance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIndicator Dimension\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnsanitary waste disposal and leachate impacts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReports on leachate leakage, soil and groundwater contamination, unpleasant odors, and health concerns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProxy indicator of environmental contamination risk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEnvironmental risk\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGaps in recycling and composting infrastructure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDelays, operational interruptions, and uncertainty regarding recycling and composting facilities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIndicator of system capacity and operational adequacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eService performance\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eContractor performance deficiencies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIrregular collection schedules, uneven spatial service coverage, and weak responsiveness to complaints\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSignal of governance effectiveness and accountability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInstitutional performance\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformal waste picking activities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedia narratives linking waste picking to poverty, marginalization, and occupational health risks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIndicator of social vulnerability and public health risk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePublic health\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic dissatisfaction with municipal services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplaints, distrust, and calls for accountability and transparency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProxy for institutional legitimacy and public trust\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGovernance \u0026amp; public trust\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe third indicator reflects dissatisfaction with private waste collection contractors. This theme was characterized by frequent references to irregular collection schedules, uneven spatial service coverage, and limited responsiveness to complaints, particularly in peripheral urban areas. The consistency of this discourse indicates that service reliability constitutes a key dimension through which governance performance is publicly evaluated. In monitoring terms, contractor-related narratives serve as indirect indicators of operational efficiency and accountability. The fourth indicator centers on informal waste picking (zobale-gardi), which emerged as a recurrent and visible topic across platforms. Media narratives frequently associated waste picking with poverty, social marginalization, and heightened health risks. The prominence of this theme positions it as a composite indicator capturing both social vulnerability and regulatory gaps within the MSW governance framework. The fifth thematic indicator reflects generalized public dissatisfaction and institutional mistrust. This theme aggregated complaints, skepticism toward announced reforms, and explicit demands for accountability. Although less directly linked to physical waste flows, this indicator captures a critical governance dimension\u0026mdash;public trust\u0026mdash;that remains largely absent from conventional MSW monitoring systems.\u003c/p\u003e \u003cp\u003eThe thematic indicators identified in this study are broadly consistent with findings from previous research applying media-based and text-analytic approaches to environmental governance and waste management. Studies conducted in rapidly urbanizing contexts have similarly reported the prominence of service reliability, waste infrastructure performance, and public dissatisfaction as dominant themes in local media discourse (Jiang et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Yandri et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Contractor performance and informal waste practices have also been highlighted as salient public-facing governance concerns in prior work (Wu et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, the present study advances this literature by explicitly operationalizing these recurrent discourse themes as monitoring-relevant indicators, rather than treating them solely as descriptive patterns. By linking thematic prominence to governance performance dimensions, the analysis provides a structured pathway for integrating media-derived signals into environmental monitoring and assessment frameworks.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eSentiment-Based Indicators and Emotional Dynamics\u003c/h2\u003e \u003cp\u003eSentiment analysis added a quantitative interpretive layer to the thematic indicators by characterizing the emotional orientation of media discourse on MSW management (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Overall, negative sentiment predominated, with anger representing 32% of the analyzed content and concern accounting for 23%. These negative emotional expressions were primarily associated with narratives describing service interruptions, environmental exposure, and perceived institutional inaction. Positive sentiment, while less prevalent, was consistently linked to reports of tangible municipal interventions. Expressions of hope (18%) and satisfaction (12%) corresponded mainly to coverage of infrastructure-related actions, including the reopening of composting facilities, the deployment of mechanized underground waste containers, and the implementation of public education initiatives. Neutral sentiment constituted approximately 15% of the corpus and was largely confined to factual or informational reporting lacking explicit evaluative judgment.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of sentiment categories in local media discourse on MSW management\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSentiment Category\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDominant Associated Themes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eService disruptions, contractor failures, environmental exposure\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConcern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLeachate contamination, public health risks\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHope\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eComposting initiatives, infrastructure improvements\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSatisfaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVisible municipal interventions\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInformational and descriptive reports\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePolarity scores derived from machine-learning classification further supported this pattern. Mean sentiment values were +\u0026thinsp;0.74 for the training dataset and +\u0026thinsp;0.68 for the test dataset, indicating that despite frequent criticism, the overall tone of the discourse remained moderately positive. Despite the dominance of negative emotions, polarity scores remained positive due to the co-occurrence of criticism with solution-oriented and improvement-related narratives. This suggests that negative evaluations were often accompanied by expressions of optimism or approval when tangible improvements were observed. Overall, the emotional profile reflects sustained public engagement rather than disengagement or hostility. From an environmental monitoring perspective, the use of media-derived indicators aligns with recent efforts to incorporate socially derived data into environmental assessment frameworks. Previous studies have demonstrated the value of indirect indicators, such as citizen reports and media narratives, in identifying governance gaps and emerging environmental risks (Zhang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Zolnoori et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Compared to earlier applications that primarily emphasized sentiment or thematic prevalence, the present study advances the field by linking thematic prominence and emotional orientation to specific dimensions of MSW system performance, including environmental exposure, service reliability, and public trust.\u003c/p\u003e \u003cp\u003eThe identified indicators provide early-warning signals of environmental exposure (unsanitary disposal and leachate), operational stress (service irregularities and infrastructure gaps), social vulnerability (waste picking), and governance performance (public trust and accountability). In practice, the timing and spatial specificity of media-derived signals depend on posting behavior and platform usage patterns, which varied across neighborhoods during the study period. When interpreted within environmental monitoring frameworks, this indicator suggests, integrating media-based indicators alongside established technical metrics can enhance the sensitivity, contextual awareness, and responsiveness of MSW monitoring systems. Such integration aligns with broader shifts in environmental governance toward participatory monitoring, transparency, and adaptive management, particularly in rapidly urbanizing settings where formal data collection may be delayed or incomplete. The thematic and sentiment-based indicators demonstrate that local digital media discourse may function as a complementary, perception-based monitoring signal. Unlike conventional monitoring systems that rely on periodic technical measurements, media-derived indicators reflect continuous public observation of environmental conditions, service performance, and institutional responsiveness.\u003c/p\u003e \u003cp\u003eThe identified indicators provide early-warning signals of environmental exposure (unsanitary disposal and leachate), operational stress (service irregularities and infrastructure gaps), social vulnerability (informal waste picking), and governance performance (public trust and accountability). Significantly, these signals emerge in near real time and capture dimensions of system performance that are directly visible to affected communities but often remain underrepresented in formal monitoring frameworks.\u003c/p\u003e \u003cp\u003eIntegrating media-based indicators alongside established technical metrics can therefore enhance the sensitivity, contextual awareness, and responsiveness of MSW monitoring systems. Such integration aligns with broader shifts in environmental governance toward participatory monitoring, transparency, and adaptive management, particularly in urban contexts where formal data collection may be delayed, fragmented, or incomplete. By translating unstructured media narratives into thematic and sentiment-based indicators, the analysis extends conventional MSW monitoring beyond technical and infrastructural metrics to include governance performance, public trust, and experiential exposure to environmental risk.\u003c/p\u003e \u003cp\u003eThe results show that recurrent media themes\u0026mdash;such as unsanitary waste disposal, infrastructure gaps, contractor performance deficiencies, informal waste picking, and institutional mistrust\u0026mdash;function as stable, monitoring-relevant signals that reflect public-facing dimensions of MSW system performance. When interpreted through an environmental monitoring lens, these themes operate as qualitative proxies for contamination risk, service reliability, institutional accountability, and social vulnerability. Unlike conventional indicators derived from periodic measurements, media-based signals emerge continuously and are grounded in lived experience, allowing emerging issues to be detected earlier and at finer spatial and temporal scales.\u003c/p\u003e \u003cp\u003eSentiment-based indicators further enhance the monitoring value of media discourse by capturing the emotional orientation associated with observed conditions and governance responses. Although negative emotions such as anger and concern were prevalent, the simultaneous presence of hope and satisfaction indicates that public criticism is often conditional rather than oppositional. From an assessment perspective, this emotional configuration reflects sustained civic engagement and responsiveness to observable improvements, rather than systemic disengagement or distrust. Such sentiment dynamics provide additional interpretive depth that is typically absent from technical monitoring datasets. While the identified themes function as monitoring-relevant signals, their interpretation depends on the activity level and representativeness of local media platforms. In less active media environments, such indicators may underestimate governance stress.\u003c/p\u003e \u003cp\u003eFrom an environmental governance standpoint, integrating media-derived indicators into MSW monitoring frameworks can enhance transparency, adaptive management, and participatory assessment. The Saveh case illustrates how media analytics can support early warning, contextual interpretation of technical data, and alignment of municipal interventions with public expectations. More broadly, this approach contributes to ongoing shifts in environmental monitoring and assessment toward hybrid systems that combine biophysical measurements with socially derived signals, particularly in rapidly urbanizing contexts where formal data collection may be delayed or incomplete.\u003c/p\u003e \u003cp\u003eThis study demonstrates the value of computational analysis of local media content for urban environmental monitoring and assessment. By revealing how environmental risks, service deficiencies, and institutional responses are perceived and communicated, media-based analysis extends conventional monitoring approaches. The results suggest that comprehensive assessment of MSW performance should integrate technical indicators with social signals embedded in public discourse, particularly in rapidly urbanizing contexts.\u003c/p\u003e \u003cp\u003e \u003cb\u003e5. 3 Interpretation of Findings in the Context of Environmental Monitoring\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe results presented above extend beyond descriptive patterns of media discourse and can be interpreted as monitoring-relevant signals within an environmental governance framework. Unlike conventional MSW monitoring systems, which primarily rely on technical and operational metrics, the indicators derived in this study reflect how environmental risks, service performance, and institutional responsiveness are perceived and evaluated by affected communities. From an environmental monitoring perspective, the persistence of themes related to unsanitary disposal practices and leachate leakage suggests that public discourse may function as an informal early-warning system. Recurrent references to odors, contamination, and health concerns indicate perceived environmental exposure that may precede or escape detection through routine technical inspections. Similar interpretive roles of citizen-generated or media-based signals have been discussed in prior monitoring-oriented studies (Zhang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Zolnoori et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn addition, themes related to service reliability and contractor performance highlight dimensions of MSW systems that are difficult to capture through infrastructure-focused indicators alone. While collection coverage or fleet capacity may appear adequate in official reports, media narratives reveal how irregularity, spatial inequality, and responsiveness shape public evaluation of system effectiveness. In this sense, media-derived indicators complement technical monitoring by capturing performance as experienced rather than as designed.\u003c/p\u003e \u003cp\u003eThe presence of waste picking as a dominant and persistent theme further illustrates the added value of discourse-based monitoring. Informal recovery activities simultaneously reflect economic vulnerability, regulatory gaps, and occupational health risks. Their visibility in local media suggests that such practices constitute a salient governance signal, even when they remain weakly represented in formal waste statistics.\u003c/p\u003e \u003cp\u003eFinally, expressions of dissatisfaction and institutional mistrust represent a governance dimension that is largely absent from conventional MSW monitoring frameworks. Although trust cannot be directly measured through physical indicators, its recurring articulation in public discourse provides insight into perceived legitimacy, accountability, and transparency. Interpreted as a monitoring signal, institutional mistrust may indicate declining system credibility and reduced public cooperation, both of which have implications for long-term system sustainability (Jiang et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wu et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eGovernance and Policy Implications\u003c/h2\u003e \u003cp\u003eThe findings demonstrate the dual governance role of local digital media within MSW systems. Media platforms function both as informal watchdogs\u0026mdash;exposing service deficiencies, environmental risks, and governance failures\u0026mdash;and as facilitators by disseminating information on corrective actions and infrastructure improvements. This balance between critical and constructive narratives appears more effective in sustaining public engagement and institutional accountability than exclusively negative framing (Bennett, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Bruns et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Fung, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFrom an assessment standpoint, the Saveh case reflects a shift toward participatory evaluation models in which MSW performance is assessed not only through technical indicators but also through responsiveness, transparency, and public perception. This approach aligns with hybrid environmental monitoring frameworks that integrate expert-driven measurements with citizen-generated and perception-based data, thereby enhancing contextual sensitivity and interpretive capacity (Conrad \u0026amp; Hilchey, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Wehn \u0026amp; Evers, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThematic analysis identified governance-relevant dimensions of MSW performance related to environmental exposure, infrastructure capacity, service reliability, social vulnerability, and public trust. Perception-based narratives on unsanitary disposal and leachate leakage function as early-warning signals of environmental and public health risks, particularly in contexts with limited formal monitoring (Hadjimitsis et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Discourse on recycling infrastructure and contractor performance highlights structural and contractual weaknesses often underrepresented in conventional MSW metrics (Guerrero et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Wilson et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), while attention to informal waste picking underscores links between MSW governance, inequality, and environmental justice (Gutberlet et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Persistent expressions of public mistrust further signal governance stress and misalignment between institutional performance and societal expectations. Despite predominantly critical narratives, constructive reporting on infrastructure upgrades and community education initiatives indicates that local media also support adaptive governance by amplifying successful interventions and encouraging cooperative public behavior (Emerson \u0026amp; Nabatchi, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e highlights the complementary role of media-derived indicators in municipal solid waste monitoring. While conventional indicators primarily capture technical and infrastructural performance, media-based indicators provide near real-time insights into governance effectiveness, public trust, and perceived environmental risks. By reflecting citizen experiences and institutional responsiveness, media discourse enhances early-warning capacity and contextual interpretation of formal monitoring data. Integrating media-derived indicators with conventional metrics therefore supports a more adaptive and comprehensive environmental monitoring framework.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAdvantages of media-based indicators compared to conventional MSW monitoring\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonitoring Aspect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConventional MSW Indicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedia-Derived Indicators\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemporal resolution\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePeriodic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNear real-time\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGovernance performance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLimited\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExplicit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic trust \u0026amp; perception\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRarely captured\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDirectly observable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEarly warning capacity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial vulnerability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOften omitted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eClearly reflected\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis work demonstrates that local digital media may function as a complementary, perception-based monitoring layer within MSW systems. It does not aim to replace technical MSW monitoring systems. Rather, it proposes media-derived indicators as supplementary signals that may enhance situational awareness, especially where conventional data are delayed or incomplete. By systematically translating unstructured media discourse into thematic and sentiment-based indicators, the analysis captures qualitative signals related to environmental risk, service reliability, institutional performance, and public trust\u0026mdash;dimensions that are often insufficiently represented in conventional, technically oriented monitoring frameworks.\u003c/p\u003e \u003cp\u003eFrom an environmental monitoring and assessment standpoint, media-derived indicators provide early-warning signals and contextual information that enhance both the sensitivity and interpretability of MSW performance assessments. Integrating such indicators alongside established technical metrics can support more adaptive, transparent, and participatory governance processes, particularly in rapidly urbanizing urban contexts where formal monitoring data may be delayed or incomplete.\u003c/p\u003e \u003cp\u003eAlthough the findings are derived from a single urban case, the proposed analytical framework is transferable to other cities with active local media ecosystems. Future research should extend this approach through comparative and longitudinal analyses, as well as by integrating media-based indicators with conventional environmental and operational datasets, to further assess their contribution to robust and responsive MSW monitoring and assessment systems.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e \u003cp\u003eThis study was conducted as part of a research project approved by the Ethics Committee of Saveh University of Medical Sciences (Ethics code: IR.SAVEHUMS.REC.1403.027). All analyzed data were obtained from publicly accessible media sources. No private, sensitive, or personally identifiable information was collected or analyzed. The study was performed in accordance with institutional and national ethical standards for research involving publicly available digital content.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eConflicts of interest\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eReza Nemati: Supervision, Project administration, Funding acquisition, Writing \u0026ndash; review \u0026amp; editing.AliReza Bagheri Resaei: Data curation, Formal analysis, Writing \u0026ndash; review \u0026amp; editing.Narges Hakimi: Conceptualization, Methodology, Investigation, Writing \u0026ndash; original draft.All authors have read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eThe authors gratefully acknowledge the support of Saveh University of Medical Sciences.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eDatasets generated and analyzed during the current study are derived from publicly available local media sources. The processed data supporting the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBennett, S. E. (2001). Pippa Norris, A Virtuous Circle: Political Communications in Postindustrial Societies. Cambridge, Cambridge University Press, 2000. \u003cem\u003eInternational Journal of Public Opinion Research\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(4), 442\u0026ndash;445. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/ijpor/13.4.442\u003c/span\u003e\u003cspan address=\"10.1093/ijpor/13.4.442\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBing, L. (2012). 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Mining news media for understanding public health concerns. \u003cem\u003eJ Clin Transl Sci\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(1), e1. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1017/cts.2019.434\u003c/span\u003e\u003cspan address=\"10.1017/cts.2019.434\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Environmental monitoring, municipal solid waste management, text mining, media-derived indicators, urban environmental governance, media-based monitoring","lastPublishedDoi":"10.21203/rs.3.rs-8525042/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8525042/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRapid urbanization has revealed significant limitations in traditional municipal solid waste (MSW) monitoring systems, especially those focusing primarily on technical and infrastructural indicators. While these approaches address operational aspects, they often overlook key dimensions like governance performance, service reliability, and public response. These aspects are critical for effective waste management but are less systematically monitored. Local digital media discourse presents an underutilized resource for real-time monitoring of these qualitative dimensions.\u003c/p\u003e \u003cp\u003eThis study conceptualizes local digital media discourse as a perception-based monitoring tool for environmental monitoring in MSW governance. A descriptive\u0026ndash;analytical text-mining design was adopted to systematically extract, structure, and interpret monitoring indicators embedded in local media content related to MSW management.\u003c/p\u003e \u003cp\u003eFive monitoring-relevant themes were identified, each reflecting distinct dimensions of environmental risk and governance performance: unsanitary waste disposal and leachate impacts; limitations in recycling and composting infrastructure; contractor performance deficiencies; waste picking activities; and public dissatisfaction with municipal services. Negative sentiments, particularly anger (32%) and concern (23%), were prominent, alongside expressions of hope (18%), satisfaction (12%), and neutral content (15%). Notably, critical narratives frequently co-occurred with concrete, improvement-oriented suggestions.\u003c/p\u003e \u003cp\u003eThe analysis indicates that local media content reflects aspects of governance performance and service-related concerns that are not routinely documented in technical MSW datasets. These signals appear particularly relevant in contexts where formal monitoring is fragmented or delayed.\u003c/p\u003e","manuscriptTitle":"Local Media–Derived Indicators for Monitoring Municipal Solid Waste Governance: A Text-Mining Assessment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-09 05:22:27","doi":"10.21203/rs.3.rs-8525042/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"55010639-07b3-480c-8ee3-03a6307429e4","owner":[],"postedDate":"January 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T15:10:10+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-09 05:22:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8525042","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8525042","identity":"rs-8525042","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}