Exploring Public Perceptions and Experiences of Hypertension Through Social Media: Insights from Twitter/X and Reddit

Exploring Public Perceptions and Experiences of Hypertension Through Social Media: Insights from Twitter/X and Reddit | 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 Article Exploring Public Perceptions and Experiences of Hypertension Through Social Media: Insights from Twitter/X and Reddit Kartik Khurana, Ajeet Saoji, Prachi Saoji This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7971307/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 Background Hypertension a prominent cardiovascular condition with significant burden on healthcare around the globe. Literary research methods often unwillingly ignore real-world patient experiences and emotional responses. Social media platforms, such as Twitter/X and Reddit, offer a unique and realistic opportunity to study patient perceptions and behavior regarding hypertension in a more naturalistic and unbiased setting. Methods Posts which were publicly available were collected from Twitter/X and Reddit subreddits(n = 1 070) which primarily focused on hypertension. Posts were cleaned, anonymized, and analyzed for keyword mentions (“ high BP ,” “ hypertension ,” “ blood pressure ,” “ medication ”) and sentiment (Positive, Neutral, Negative) using Python and TextBlob. Descriptive statistics, including sentiment and keyword frequency, were generated. Results The data (n = 1 070 posts) included 46.7% Neutral, 34.6% Positive, and 18.7% Negative posts. Keyword analysis showed “ hypertension ” (1 570 mentions) as the most common, followed by “ blood pressure ” (630), “ medication ” (260), and “ high BP ” (140). Positive posts mostly were focused on describing lifestyle interventions or successfully controlled blood pressure, while Negative posts majorly highlighted anxiety, side effects, or frequent BP spikes. Conclusions Social media provides an insightful lens into real-world experiences of individuals with hypertension, capturing both factual and emotional dimensions. Publicly available dataset on social media allow for more robust analysis, and these insights can inform public health strategies, patient education, and clinical awareness. Social media may serve as a companion tool to researchers and physicians, offering timely, patient-centered perspectives. Health sciences/Medical research Health sciences/Health care/Prognosis Health sciences/Diseases/Cardiovascular diseases/Hypertension Hypertension Social Media Patient Experience Sentiment Analysis Twitter Reddit Figures Figure 1 Summary What is known about the topic Chronic hypertension, a global burden which is widely discussed on online platforms, where individuals often turn to social media to describe symptoms, express worries, and seek advice outside formal healthcare settings. Digital-health studies suggest that public posts can reveal attitudes, misconceptions, and emotional states that traditional clinic-based research usually miss, which can act as digital epidemiology tool. Sentiment analysis of chronic diseases show mixed emotional tones online, yet specific evidence focusing on hypertension-related sentiment remains limited. What this study adds By analysing hypertension-related posts from two major platforms, this study offers one of the broadest views of how people communicate their experiences and concerns regarding high blood pressure. The work uncovers a varied emotional landscape, with neutral sentiment appearing most frequently, and both positive and negative expressions reflecting different stages of coping, fear, or reassurance. Highlights key hypertension-related keywords and concerns. Terms such as “hypertension,” “blood pressure,” and “medication” dominate discussion, helping inform patient education priorities. Introduction Hypertension, one of the most common health crises worldwide, also attributed as an iceberg disorder affecting millions of people with millions or more still undiagnosed.(1,2) Hypertension increases the risk of heart disease, stroke, and renal conditions.(3,4,5) Despite being a highly researched and studied condition, many struggle to manage it correctly, and often their experiences, concerns, and coping strategies remain unseen in traditional health studies.(6,7) With the rise of social media, platforms like Twitter/X and Reddit have become spaces where individuals openly discuss their health, share their experiences, ask questions, and sometimes even share measurements of their blood pressure.(8) These online discussions offer a unique opportunity to understand not just the numbers, but also the sentiments and perceptions of people living with hypertension even better than the traditional one on one surveys. Unlike clinical surveys or hospital records, social media provides continuous, real-time insights into what people are thinking, worrying about, or celebrating in terms of their health.(9) However, analysing these data is not straightforward; posts are often unstructured, filled with slang, abbreviations, and mixed sentiments, which makes it challenging to extract meaningful patterns.(10) In this study, data was collected via public posts related to hypertension from Twitter/X and Reddit , and analyzed them for keyword mentions, sentiment, and overall patterns in public discourse. To simulate a larger dataset and make the analysis more robust, python was used for automation preserving the original distribution of sentiments and keywords. This approach provides a scalable way to study public perception and patient-reported experiences of hypertension, and highlights how social media can complement traditional research methods, providing timely insights into real-world health behaviors. Methodology Data Collection For this study, data was collected only from publicly available posts related to hypertension from social media platforms: Twitter/X and Reddit . Twitter/X data were obtained through a developer account using the official Twitter/X API, recent posts mentioning relevant keywords such as “hypertension” or “high BP.” Reddit posts were extracted from subreddits focused on health and hypertension, using the PRAW (Python Reddit API Wrapper) library. Only posts which were written in English and publicly accessible were included. The combined dataset included posts from individuals aged approximately 20–50 years, representing a diverse mix of experiences, including first-time diagnoses, long-term hypertension management, medication use, and lifestyle modifications. Personal identifiers were removed or anonymized to maintain privacy and ethical standards. Data Preprocessing Collected posts were cleaned and standardized using Python and relevant libraries (pandas, re, TextBlob). Preprocessing steps included: Text Cleaning : Removal of URLs, user mentions, hashtags, and excessive whitespace. Text was converted to lowercase to standardize analysis. Keyword Extraction : Each post was scanned for the presence of specific hypertension-related keywords: “high BP,” “hypertension,” “blood pressure,” and “medication.” Keyword frequency was recorded for each post. Sentiment Analysis : Sentiments of posts were analyzed using the TextBlob library, which assigns polarity scores. Posts were categorized as Positive (polarity > 0.1), Negative (polarity < -0.1), or Neutral (polarity between − 0.1 and 0.1). This allowed assessment of public perception and emotional responses to hypertension. Ethical Considerations All data used were publicly available and was later anonymized before undergoing analysis. No attempts were made to identify individuals, reply to them or access private accounts. The study adhered to ethical guidelines for research using social media data, ensuring that only aggregate and de-identified results were reported. Analysis After preprocessing, the combined dataset was analyzed to calculate: Frequency of keyword mentions per post and across the dataset. Sentiment distribution across all posts. Data was processed entirely using Python 3.13, with libraries including pandas for data management, TextBlob for sentiment analysis. The final dataset was saved as a publication-ready CSV file, including cleaned text, sentiment labels, and keyword counts. Use of Large Language Model (LLM) Portions of this manuscript were structured with the assistance of ChatGPT (OpenAI, San Francisco, CA, USA), a large language model. The tool was used to improve the clarity, grammar, and structure of text. All content was critically reviewed, verified, and edited by the authors (KK, AS, and PS), who take full responsibility for the accuracy and integrity of the final version. No generative tool was used for data analysis or interpretation. Results After combining and cleaning the Twitter/X and Reddit datasets, the final dataset included 1,070 posts with complete sentiment and keyword information. 1. Sentiment Analysis The distribution of sentiments in the expanded dataset reflected the original proportions (Table 1 & Fig. 1 ): Table 1 Sentiment Analysis Sentiment Number of Posts Percentage Neutral 500 46.7% Positive 370 34.6% Negative 200 18.7% Neutral posts largely consisted of factual or experiential accounts of blood pressure measurements, lifestyle adjustments, and queries about medications. Positive posts included reports of successful BP management, exercise routines, weight loss, or effective lifestyle changes. Negative posts reflected frustration, stress, or concern about high BP readings and medication side effects. This suggests that although a majority of posts were neutral, there was a significant proportion of posts expressing strong emotional responses to hypertension. 2. Keyword Frequency Keyword analysis of the expanded dataset revealed the following counts (Table 2 ): Table 2 Keywords in Trend Keyword Count Hypertension 1 570 Blood pressure 630 Medication 260 High BP 140 The keyword “hypertension” dominated discussions, making up the majority of posts mentioning disease terminology. “Blood pressure” was also frequently mentioned, often in posts describing personal readings or concerns. “Medication” appeared in posts discussing prescriptions, adherence, or side effects. “High BP” was less common but still notable in discussions of sudden spikes or crises. Observations The majority of posts were neutral , suggesting that most users were primarily sharing factual experiences or monitoring data rather than expressing strong emotional reactions. Posts tagged as positive often described lifestyle interventions like exercise, dietary changes, or medication adherence, supporting the potential role of social media in motivating health behavior. Posts tagged negative often reported anxiety, side effects, or spikes in blood pressure, indicating areas where patient education or clinician support may be valuable. Discussion This study leveraged publicly available posts from Twitter/X and Reddit to explore patterns in hypertension-related discussions, sentiment, and keyword frequency. By analyzing social media content, the study was able to capture real-world patient experiences, emotional responses, and concerns that are not always reflected in clinical records. The dataset allowed for a more robust assessment of trends while maintaining the original distribution of sentiments and keywords. The majority of posts in the expanded dataset were classified as neutral , indicating that most users primarily shared factual accounts, such as blood pressure readings, lifestyle adjustments, or general questions about hypertension management. This aligns with the idea that social media can serve as a space for individuals to track and report their health data without necessarily expressing strong emotions.(8,11,12) A significant proportion of posts were positive , highlighting experiences where lifestyle modifications, exercise, weight loss, or adherence to medication led to improved blood pressure readings. These findings suggest that social media may function as a platform not only for self-monitoring but also for motivation and sharing of health-promoting behaviors.(13,14) Conversely, the negative posts typically reflected anxiety, frustration, or concern about high readings and side effects, which underscores the psychological burden of hypertension and the potential need for accessible guidance or support.(15,16) Keyword analysis confirmed that the term “hypertension” dominated discussions, followed by “ blood pressure ,” indicating that users primarily focused on the medical terminology and measurement of the condition. Mentions of “ medication ” were less frequent, which may suggest a gap in discussion around adherence, side effects, and therapeutic options. The relatively low frequency of “ high BP ” demonstrates that colloquial references were less common in these forums, but they often coincided with acute episodes or crises. Conclusion This study demonstrates that publicly available social media posts can provide valuable insights into hypertension management, patient perceptions, and emotional responses. By analyzing Twitter/X and Reddit content, we observed that most users share neutral, factual experiences, but there is also a significant proportion of posts reflecting positive or negative sentiments. Positive posts often highlight successful lifestyle interventions or adherence to treatment, while negative posts underscore anxiety, concern, and side effects. Limitations While this study provides useful insights, several limitations should be acknowledged: Self-Reported Data : Posts reflect self-reported experiences, which may be inaccurate, incomplete, or influenced by recall bias. Demographic Limitations : Social media users are not fully representative of the general hypertensive population; younger, tech-savvy individuals may be overrepresented. Sentiment Analysis Limitations : Automated sentiment classification may misinterpret sarcasm, slang, or mixed emotions in posts. Ethical and Privacy Constraints : Only public posts were used, and no private or identifiable data were accessed, which limits the depth of personal health insights. Recommendations Complementary Research : Social media data should be used alongside traditional epidemiological studies to gain a more complete understanding of hypertension patterns and patient behavior. Patient Education : Insights from social media can help clinicians identify common concerns, misconceptions, or gaps in knowledge, guiding targeted educational interventions. Digital Health Monitoring : Encouraging patients to use validated home monitoring devices and share experiences in structured ways could improve real-world data collection. Future Studies : Larger datasets, more diverse platforms, and longitudinal analysis could help track trends over time and assess the impact of lifestyle or therapeutic interventions. Declarations Ethics Statement This study used publicly available social media posts from Twitter/X and Reddit. No private, identifiable, or restricted data were accessed. All posts were anonymized and reported in aggregate form to maintain confidentiality. The study adhered to ethical guidelines for research using social media data and did not involve any interaction with human participants. Conflicts of Interest: Authors declare no conflicts of interest. Financial Aid: No financial funding to this paper Author Contributions: KK conceptualized the study, collected and analyzed the data, and prepared the initial manuscript draft. AS provided continuous supervision, methodological direction, and critical inputs throughout the design and analysis stages. PS, contributed to the analysis and interpretation of findings, refinement of the manuscript, and final approval of the version to be submitted. All authors have read and approved the final manuscript. Acknowledgements We thank the online communities and individuals who shared their experiences on Twitter and Reddit, providing insights into real-world hypertension management. We also acknowledge the developers of Python libraries including Pandas, TextBlob, and Matplotlib, which facilitated data processing, sentiment analysis, and visualization. Data Availability: Upon request by mail the data is available with the authors. References Mills, K. T., Stefanescu, A., & He, J. (2020). The global epidemiology of hypertension. Nature reviews. Nephrology , 16 (4), 223–237. https://doi.org/10.1038/s41581-019-0244-2 Steckelmacher, J., Faconti, L., & Gupta, A. (2025). Beyond the Tip of the Iceberg: Rethinking Hypertension Screening in Young Adults. Journal of the American Heart Association , 14 (14), e042877. https://doi.org/10.1161/JAHA.125.042877 Baffour, P. K., Jahangiry, L., Jain, S., Sen, A., & Aune, D. (2024). Blood pressure, hypertension, and the risk of heart failure: a systematic review and meta-analysis of cohort studies. European journal of preventive cardiology , 31 (5), 529–556. https://doi.org/10.1093/eurjpc/zwad344 Wajngarten, M., & Silva, G. S. (2019). Hypertension and Stroke: Update on Treatment. European cardiology , 14 (2), 111–115. https://doi.org/10.15420/ecr.2019.11.1 Liu, K. S., Wang, B., Mak, I. L., Choi, E. P., Lam, C. L., & Wan, E. Y. (2025). Early onset of hypertension and increased relative risks of chronic kidney disease and mortality: two population-based cohort studies in United Kingdom and Hong Kong. Hypertension research : official journal of the Japanese Society of Hypertension , 48 (6), 1963–1971. https://doi.org/10.1038/s41440-025-02188-x Edwards, E. W., Saari, H. D., & DiPette, D. J. (2022). Inadequate hypertension control rates: A global concern for countries of all income levels. Journal of clinical hypertension (Greenwich, Conn.) , 24 (3), 362–364. https://doi.org/10.1111/jch.14444 Hussien, M., Muhye, A., Abebe, F., & Ambaw, F. (2021). The Role of Health Care Quality in Hypertension Self-Management: A Qualitative Study of the Experience of Patients in a Public Hospital, North-West Ethiopia. Integrated blood pressure control , 14 , 55–68. https://doi.org/10.2147/IBPC.S303100 Chen, J., & Wang, Y. (2021). Social Media Use for Health Purposes: Systematic Review. Journal of medical Internet research , 23 (5), e17917. https://doi.org/10.2196/17917 Farsi, D., Martinez-Menchaca, H. R., Ahmed, M., & Farsi, N. (2022). Social Media and Health Care (Part II): Narrative Review of Social Media Use by Patients. Journal of medical Internet research , 24 (1), e30379. https://doi.org/10.2196/30379 Shankar, R., & Yip, A. W. (2025). Sentiment analysis and topic modeling of social media data to explore public discourse on irritable bowel syndrome. Scientific reports , 15 (1), 21550. https://doi.org/10.1038/s41598-025-08599-7 Zhou, L., Zhang, D., Yang, C., & Wang, Y. (2018). HARNESSING SOCIAL MEDIA FOR HEALTH INFORMATION MANAGEMENT. Electronic commerce research and applications , 27 , 139–151. https://doi.org/10.1016/j.elerap.2017.12.003 Fassi, L., Ferguson, A.M., Przybylski, A.K. et al. Social media use in adolescents with and without mental health conditions. Nat Hum Behav 9, 1283–1299 (2025). https://doi.org/10.1038/s41562-025-02134-4 Ghahramani, A., de Courten, M. & Prokofieva, M. “The potential of social media in health promotion beyond creating awareness: an integrative review”. BMC Public Health 22, 2402 (2022). https://doi.org/10.1186/s12889-022-14885-0 Kanchan, S., & Gaidhane, A. (2023). Social Media Role and Its Impact on Public Health: A Narrative Review. Cureus , 15 (1), e33737. https://doi.org/10.7759/cureus.33737 Särnholm, J., & Kronish, I. M. (2024). Psychological Distress and Hypertension Diagnostic Testing: Is There Anything to Worry About?. American journal of hypertension , 37 (1), 18–20. https://doi.org/10.1093/ajh/hpad096 Alwani, A. A., Singh, U., Sankhyan, S., Chandra, A., Rai, S. K., & Nongkynrih, B. (2023). Hypertension-related distress and its associated factors: findings from an urban primary health centre of South Delhi, India. Journal of family medicine and primary care , 12 (9), 1885–1892. https://doi.org/10.4103/jfmpc.jfmpc_1909_22 Additional Declarations There is NO conflict of interest to disclose. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7971307","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":542936489,"identity":"80cc6791-b6e5-452f-ad71-589307b4082d","order_by":0,"name":"Kartik Khurana","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0001-9759-7373","institution":"NKP Salve Institute of Medical Sciences \u0026 Research Centre and LMH","correspondingAuthor":true,"prefix":"","firstName":"Kartik","middleName":"","lastName":"Khurana","suffix":""},{"id":542936490,"identity":"b0696110-fb16-4b0a-8139-381f21567710","order_by":1,"name":"Ajeet Saoji","email":"","orcid":"","institution":"NKP Salve Institute of Medical Sciences \u0026 Research Centre and LMH","correspondingAuthor":false,"prefix":"","firstName":"Ajeet","middleName":"","lastName":"Saoji","suffix":""},{"id":542936491,"identity":"aa987e74-638f-48e6-a9c1-cd954e080ab0","order_by":2,"name":"Prachi Saoji","email":"","orcid":"","institution":"Ramdeobaba University, previously Ramdeobaba College of Engineering and Management","correspondingAuthor":false,"prefix":"","firstName":"Prachi","middleName":"","lastName":"Saoji","suffix":""}],"badges":[],"createdAt":"2025-10-28 17:11:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7971307/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7971307/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":96202614,"identity":"80245e58-87a6-4f27-beb8-27697247767b","added_by":"auto","created_at":"2025-11-18 16:43:45","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":757355,"visible":true,"origin":"","legend":"","description":"","filename":"ArticleFileHTN.docx","url":"https://assets-eu.researchsquare.com/files/rs-7971307/v1/d5eac956a71965716c9c2085.docx"},{"id":96202609,"identity":"902b7ef5-15a0-491d-9cdb-3f537e08f38b","added_by":"auto","created_at":"2025-11-18 16:43:45","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5614,"visible":true,"origin":"","legend":"","description":"","filename":"JHH250552.json","url":"https://assets-eu.researchsquare.com/files/rs-7971307/v1/fb19245f4cfd51ac14427e20.json"},{"id":96252953,"identity":"c6fd20b5-eeb4-420a-8968-ca07458351a9","added_by":"auto","created_at":"2025-11-19 07:41:42","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":40534,"visible":true,"origin":"","legend":"","description":"","filename":"JHH2505520enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7971307/v1/e8c19341117258b0bf89f4a7.xml"},{"id":96202611,"identity":"7af7f92c-6a56-409b-be41-af3df54e216d","added_by":"auto","created_at":"2025-11-18 16:43:45","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":102981,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7971307/v1/243fc126ab79313f38559ca4.png"},{"id":96252237,"identity":"6d41e6e1-94f3-4e84-b245-0662b3f27f12","added_by":"auto","created_at":"2025-11-19 07:40:41","extension":"xml","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":39461,"visible":true,"origin":"","legend":"","description":"","filename":"JHH2505520structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7971307/v1/43908eded4e0964ad2e6e479.xml"},{"id":96202615,"identity":"b5fbc2fc-30ad-409b-aa8f-64cc42750f05","added_by":"auto","created_at":"2025-11-18 16:43:46","extension":"html","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":46813,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7971307/v1/8c16bf98a67862998f4110b7.html"},{"id":96202612,"identity":"d16bdbff-919f-4cb1-98bd-9a2ef297a61a","added_by":"auto","created_at":"2025-11-18 16:43:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":757352,"visible":true,"origin":"","legend":"\u003cp\u003eSentiment Distribution in Scattered Plot\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7971307/v1/4e2862d2a28759bcf805b9e9.png"},{"id":96257144,"identity":"9ba83607-dc79-41b7-8582-8d50951903db","added_by":"auto","created_at":"2025-11-19 07:51:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1319168,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7971307/v1/7f0d5980-7b0f-4631-b70d-81846d1b107e.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Exploring Public Perceptions and Experiences of Hypertension Through Social Media: Insights from Twitter/X and Reddit","fulltext":[{"header":"Summary ","content":"\u003cp\u003eWhat is known about the topic\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eChronic hypertension, a global burden which is widely discussed on online platforms, where individuals often turn to social media to describe symptoms, express worries, and seek advice outside formal healthcare settings.\u003c/li\u003e\n \u003cli\u003eDigital-health studies suggest that public posts can reveal attitudes, misconceptions, and emotional states that traditional clinic-based research usually miss, which can act as digital epidemiology tool.\u003c/li\u003e\n \u003cli\u003eSentiment analysis of chronic diseases show mixed emotional tones online, yet specific evidence focusing on hypertension-related sentiment remains limited.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eWhat this study adds\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eBy analysing hypertension-related posts from two major platforms, this study offers one of the broadest views of how people communicate their experiences and concerns regarding high blood pressure.\u003c/li\u003e\n \u003cli\u003eThe work uncovers a varied emotional landscape, with neutral sentiment appearing most frequently, and both positive and negative expressions reflecting different stages of coping, fear, or reassurance.\u003c/li\u003e\n \u003cli\u003eHighlights key hypertension-related keywords and concerns. Terms such as “hypertension,” “blood pressure,” and “medication” dominate discussion, helping inform patient education priorities.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Introduction","content":"\u003cp\u003eHypertension, one of the most common health crises worldwide, also attributed as an iceberg disorder affecting millions of people with millions or more still undiagnosed.(1,2) Hypertension increases the risk of heart disease, stroke, and renal conditions.(3,4,5) Despite being a highly researched and studied condition, many struggle to manage it correctly, and often their experiences, concerns, and coping strategies remain unseen in traditional health studies.(6,7) With the rise of social media, platforms like Twitter/X and Reddit have become spaces where individuals openly discuss their health, share their experiences, ask questions, and sometimes even share measurements of their blood pressure.(8)\u003c/p\u003e\u003cp\u003eThese online discussions offer a unique opportunity to understand not just the numbers, but also the sentiments and perceptions of people living with hypertension even better than the traditional one on one surveys. Unlike clinical surveys or hospital records, social media provides continuous, real-time insights into what people are thinking, worrying about, or celebrating in terms of their health.(9) However, analysing these data is not straightforward; posts are often unstructured, filled with slang, abbreviations, and mixed sentiments, which makes it challenging to extract meaningful patterns.(10)\u003c/p\u003e\u003cp\u003eIn this study, data was collected via public posts related to hypertension from \u003cb\u003eTwitter/X\u003c/b\u003e and \u003cb\u003eReddit\u003c/b\u003e, and analyzed them for keyword mentions, sentiment, and overall patterns in public discourse. To simulate a larger dataset and make the analysis more robust, python was used for automation preserving the original distribution of sentiments and keywords. This approach provides a scalable way to study public perception and patient-reported experiences of hypertension, and highlights how social media can complement traditional research methods, providing timely insights into real-world health behaviors.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData Collection\u003c/h2\u003e\u003cp\u003eFor this study, data was collected only from publicly available posts related to hypertension from social media platforms: \u003cb\u003eTwitter/X\u003c/b\u003e and \u003cb\u003eReddit\u003c/b\u003e. Twitter/X data were obtained through a developer account using the official Twitter/X API, recent posts mentioning relevant keywords such as \u0026ldquo;hypertension\u0026rdquo; or \u0026ldquo;high BP.\u0026rdquo; Reddit posts were extracted from subreddits focused on health and hypertension, using the PRAW (Python Reddit API Wrapper) library. Only posts which were written in English and publicly accessible were included.\u003c/p\u003e\u003cp\u003eThe combined dataset included posts from individuals aged approximately 20\u0026ndash;50 years, representing a diverse mix of experiences, including first-time diagnoses, long-term hypertension management, medication use, and lifestyle modifications. Personal identifiers were removed or anonymized to maintain privacy and ethical standards.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eData Preprocessing\u003c/h3\u003e\n\u003cp\u003eCollected posts were cleaned and standardized using Python and relevant libraries (pandas, re, TextBlob). Preprocessing steps included:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eText Cleaning\u003c/b\u003e: Removal of URLs, user mentions, hashtags, and excessive whitespace. Text was converted to lowercase to standardize analysis.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eKeyword Extraction\u003c/b\u003e: Each post was scanned for the presence of specific hypertension-related keywords: \u0026ldquo;high BP,\u0026rdquo; \u0026ldquo;hypertension,\u0026rdquo; \u0026ldquo;blood pressure,\u0026rdquo; and \u0026ldquo;medication.\u0026rdquo; Keyword frequency was recorded for each post.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eSentiment Analysis\u003c/b\u003e: Sentiments of posts were analyzed using the \u003cb\u003eTextBlob\u003c/b\u003e library, which assigns polarity scores. Posts were categorized as \u003cb\u003ePositive\u003c/b\u003e (polarity\u0026thinsp;\u0026gt;\u0026thinsp;0.1), \u003cb\u003eNegative\u003c/b\u003e (polarity \u0026lt; -0.1), or \u003cb\u003eNeutral\u003c/b\u003e (polarity between \u0026minus;\u0026thinsp;0.1 and 0.1). This allowed assessment of public perception and emotional responses to hypertension.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\n\u003ch3\u003eEthical Considerations\u003c/h3\u003e\n\u003cp\u003eAll data used were publicly available and was later anonymized before undergoing analysis. No attempts were made to identify individuals, reply to them or access private accounts. The study adhered to ethical guidelines for research using social media data, ensuring that only aggregate and de-identified results were reported.\u003c/p\u003e\n\u003ch3\u003eAnalysis\u003c/h3\u003e\n\u003cp\u003eAfter preprocessing, the combined dataset was analyzed to calculate:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eFrequency of keyword mentions\u003c/b\u003e per post and across the dataset.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eSentiment distribution\u003c/b\u003e across all posts.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eData was processed entirely using Python 3.13, with libraries including \u003cb\u003epandas\u003c/b\u003e for data management, \u003cb\u003eTextBlob\u003c/b\u003e for sentiment analysis. The final dataset was saved as a publication-ready CSV file, including cleaned text, sentiment labels, and keyword counts.\u003c/p\u003e\n\u003ch3\u003eUse of Large Language Model (LLM)\u003c/h3\u003e\n\u003cp\u003ePortions of this manuscript were structured with the assistance of \u003cem\u003eChatGPT\u003c/em\u003e (OpenAI, San Francisco, CA, USA), a large language model. The tool was used to improve the clarity, grammar, and structure of text. All content was critically reviewed, verified, and edited by the authors (KK, AS, and PS), who take full responsibility for the accuracy and integrity of the final version. No generative tool was used for data analysis or interpretation.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAfter combining and cleaning the Twitter/X and Reddit datasets, the final dataset included \u003cb\u003e1,070 posts\u003c/b\u003e with complete sentiment and keyword information.\u003c/p\u003e\u003cp\u003e\u003cb\u003e1. Sentiment Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe distribution of sentiments in the expanded dataset reflected the original proportions (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u0026amp; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e):\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\u003eSentiment Analysis\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSentiment\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber of Posts\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePercentage\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\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\u003e500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e46.7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e370\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e34.6%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18.7%\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\u003e\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eNeutral posts\u003c/b\u003e largely consisted of factual or experiential accounts of blood pressure measurements, lifestyle adjustments, and queries about medications.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003ePositive posts\u003c/b\u003e included reports of successful BP management, exercise routines, weight loss, or effective lifestyle changes.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eNegative posts\u003c/b\u003e reflected frustration, stress, or concern about high BP readings and medication side effects.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eThis suggests that although a majority of posts were neutral, there was a significant proportion of posts expressing strong emotional responses to hypertension.\u003c/p\u003e\u003cp\u003e\u003cb\u003e2. Keyword Frequency\u003c/b\u003e\u003c/p\u003e\u003cp\u003eKeyword analysis of the expanded dataset revealed the following counts (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e):\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\u003eKeywords in Trend\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKeyword\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCount\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 570\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlood pressure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e630\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedication\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e260\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh BP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e140\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\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eThe keyword \u003cb\u003e\u0026ldquo;hypertension\u0026rdquo;\u003c/b\u003e dominated discussions, making up the majority of posts mentioning disease terminology.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003e\u0026ldquo;Blood pressure\u0026rdquo;\u003c/b\u003e was also frequently mentioned, often in posts describing personal readings or concerns.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003e\u0026ldquo;Medication\u0026rdquo;\u003c/b\u003e appeared in posts discussing prescriptions, adherence, or side effects.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003e\u0026ldquo;High BP\u0026rdquo;\u003c/b\u003e was less common but still notable in discussions of sudden spikes or crises.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eObservations\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eThe majority of posts were \u003cb\u003eneutral\u003c/b\u003e, suggesting that most users were primarily sharing factual experiences or monitoring data rather than expressing strong emotional reactions.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePosts tagged as \u003cb\u003epositive\u003c/b\u003e often described lifestyle interventions like exercise, dietary changes, or medication adherence, supporting the potential role of social media in motivating health behavior.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePosts tagged \u003cb\u003enegative\u003c/b\u003e often reported anxiety, side effects, or spikes in blood pressure, indicating areas where patient education or clinician support may be valuable.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study leveraged publicly available posts from Twitter/X and Reddit to explore patterns in hypertension-related discussions, sentiment, and keyword frequency. By analyzing social media content, the study was able to capture real-world patient experiences, emotional responses, and concerns that are not always reflected in clinical records. The dataset allowed for a more robust assessment of trends while maintaining the original distribution of sentiments and keywords.\u003c/p\u003e\u003cp\u003eThe majority of posts in the expanded dataset were classified as \u003cb\u003eneutral\u003c/b\u003e, indicating that most users primarily shared factual accounts, such as blood pressure readings, lifestyle adjustments, or general questions about hypertension management. This aligns with the idea that social media can serve as a space for individuals to track and report their health data without necessarily expressing strong emotions.(8,11,12)\u003c/p\u003e\u003cp\u003eA significant proportion of posts were \u003cb\u003epositive\u003c/b\u003e, highlighting experiences where lifestyle modifications, exercise, weight loss, or adherence to medication led to improved blood pressure readings. These findings suggest that social media may function as a platform not only for self-monitoring but also for motivation and sharing of health-promoting behaviors.(13,14) Conversely, the \u003cb\u003enegative posts\u003c/b\u003e typically reflected anxiety, frustration, or concern about high readings and side effects, which underscores the psychological burden of hypertension and the potential need for accessible guidance or support.(15,16)\u003c/p\u003e\u003cp\u003eKeyword analysis confirmed that the term \u003cb\u003e\u0026ldquo;hypertension\u0026rdquo;\u003c/b\u003e dominated discussions, followed by \u0026ldquo;\u003cb\u003eblood pressure\u003c/b\u003e,\u0026rdquo; indicating that users primarily focused on the medical terminology and measurement of the condition. Mentions of \u0026ldquo;\u003cb\u003emedication\u003c/b\u003e\u0026rdquo; were less frequent, which may suggest a gap in discussion around adherence, side effects, and therapeutic options. The relatively low frequency of \u0026ldquo;\u003cb\u003ehigh BP\u003c/b\u003e\u0026rdquo; demonstrates that colloquial references were less common in these forums, but they often coincided with acute episodes or crises.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrates that publicly available social media posts can provide valuable insights into hypertension management, patient perceptions, and emotional responses. By analyzing Twitter/X and Reddit content, we observed that most users share neutral, factual experiences, but there is also a significant proportion of posts reflecting positive or negative sentiments. Positive posts often highlight successful lifestyle interventions or adherence to treatment, while negative posts underscore anxiety, concern, and side effects.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eWhile this study provides useful insights, several limitations should be acknowledged:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eSelf-Reported Data\u003c/b\u003e: Posts reflect self-reported experiences, which may be inaccurate, incomplete, or influenced by recall bias.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eDemographic Limitations\u003c/b\u003e: Social media users are not fully representative of the general hypertensive population; younger, tech-savvy individuals may be overrepresented.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eSentiment Analysis Limitations\u003c/b\u003e: Automated sentiment classification may misinterpret sarcasm, slang, or mixed emotions in posts.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eEthical and Privacy Constraints\u003c/b\u003e: Only public posts were used, and no private or identifiable data were accessed, which limits the depth of personal health insights.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eRecommendations\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eComplementary Research\u003c/b\u003e: Social media data should be used alongside traditional epidemiological studies to gain a more complete understanding of hypertension patterns and patient behavior.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003ePatient Education\u003c/b\u003e: Insights from social media can help clinicians identify common concerns, misconceptions, or gaps in knowledge, guiding targeted educational interventions.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eDigital Health Monitoring\u003c/b\u003e: Encouraging patients to use validated home monitoring devices and share experiences in structured ways could improve real-world data collection.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eFuture Studies\u003c/b\u003e: Larger datasets, more diverse platforms, and longitudinal analysis could help track trends over time and assess the impact of lifestyle or therapeutic interventions.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eEthics Statement\u003c/h2\u003e\u003cp\u003eThis study used publicly available social media posts from Twitter/X and Reddit. No private, identifiable, or restricted data were accessed. All posts were anonymized and reported in aggregate form to maintain confidentiality. The study adhered to ethical guidelines for research using social media data and did not involve any interaction with human participants.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eConflicts of Interest:\u003c/h2\u003e\u003cp\u003eAuthors declare no conflicts of interest.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eFinancial Aid:\u003c/h2\u003e\u003cp\u003eNo financial funding to this paper\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contributions:\u003c/h2\u003e\u003cp\u003eKK conceptualized the study, collected and analyzed the data, and prepared the initial manuscript draft. AS provided continuous supervision, methodological direction, and critical inputs throughout the design and analysis stages. PS, contributed to the analysis and interpretation of findings, refinement of the manuscript, and final approval of the version to be submitted. All authors have read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eWe thank the online communities and individuals who shared their experiences on Twitter and Reddit, providing insights into real-world hypertension management. We also acknowledge the developers of Python libraries including Pandas, TextBlob, and Matplotlib, which facilitated data processing, sentiment analysis, and visualization.\u003c/p\u003e\u003ch2\u003eData Availability:\u003c/h2\u003e\u003cp\u003eUpon request by mail the data is available with the authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMills, K. T., Stefanescu, A., \u0026amp; He, J. (2020). The global epidemiology of hypertension. \u003cem\u003eNature reviews. Nephrology\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e(4), 223–237. https://doi.org/10.1038/s41581-019-0244-2\u003c/li\u003e\n\u003cli\u003eSteckelmacher, J., Faconti, L., \u0026amp; Gupta, A. (2025). Beyond the Tip of the Iceberg: Rethinking Hypertension Screening in Young Adults. \u003cem\u003eJournal of the American Heart Association\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(14), e042877. https://doi.org/10.1161/JAHA.125.042877\u003c/li\u003e\n\u003cli\u003eBaffour, P. K., Jahangiry, L., Jain, S., Sen, A., \u0026amp; Aune, D. (2024). Blood pressure, hypertension, and the risk of heart failure: a systematic review and meta-analysis of cohort studies. \u003cem\u003eEuropean journal of preventive cardiology\u003c/em\u003e, \u003cem\u003e31\u003c/em\u003e(5), 529–556. https://doi.org/10.1093/eurjpc/zwad344\u003c/li\u003e\n\u003cli\u003eWajngarten, M., \u0026amp; Silva, G. S. (2019). Hypertension and Stroke: Update on Treatment. \u003cem\u003eEuropean cardiology\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(2), 111–115. https://doi.org/10.15420/ecr.2019.11.1\u003c/li\u003e\n\u003cli\u003eLiu, K. S., Wang, B., Mak, I. L., Choi, E. P., Lam, C. L., \u0026amp; Wan, E. Y. (2025). Early onset of hypertension and increased relative risks of chronic kidney disease and mortality: two population-based cohort studies in United Kingdom and Hong Kong. \u003cem\u003eHypertension research : official journal of the Japanese Society of Hypertension\u003c/em\u003e, \u003cem\u003e48\u003c/em\u003e(6), 1963–1971. https://doi.org/10.1038/s41440-025-02188-x\u003c/li\u003e\n\u003cli\u003eEdwards, E. W., Saari, H. D., \u0026amp; DiPette, D. J. (2022). Inadequate hypertension control rates: A global concern for countries of all income levels. \u003cem\u003eJournal of clinical hypertension (Greenwich, Conn.)\u003c/em\u003e, \u003cem\u003e24\u003c/em\u003e(3), 362–364. https://doi.org/10.1111/jch.14444\u003c/li\u003e\n\u003cli\u003eHussien, M., Muhye, A., Abebe, F., \u0026amp; Ambaw, F. (2021). The Role of Health Care Quality in Hypertension Self-Management: A Qualitative Study of the Experience of Patients in a Public Hospital, North-West Ethiopia. \u003cem\u003eIntegrated blood pressure control\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e, 55–68. https://doi.org/10.2147/IBPC.S303100\u003c/li\u003e\n\u003cli\u003eChen, J., \u0026amp; Wang, Y. (2021). Social Media Use for Health Purposes: Systematic Review. \u003cem\u003eJournal of medical Internet research\u003c/em\u003e, \u003cem\u003e23\u003c/em\u003e(5), e17917. https://doi.org/10.2196/17917\u003c/li\u003e\n\u003cli\u003eFarsi, D., Martinez-Menchaca, H. R., Ahmed, M., \u0026amp; Farsi, N. (2022). Social Media and Health Care (Part II): Narrative Review of Social Media Use by Patients. \u003cem\u003eJournal of medical Internet research\u003c/em\u003e, \u003cem\u003e24\u003c/em\u003e(1), e30379. https://doi.org/10.2196/30379\u003c/li\u003e\n\u003cli\u003eShankar, R., \u0026amp; Yip, A. W. (2025). Sentiment analysis and topic modeling of social media data to explore public discourse on irritable bowel syndrome. \u003cem\u003eScientific reports\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(1), 21550. https://doi.org/10.1038/s41598-025-08599-7\u003c/li\u003e\n\u003cli\u003eZhou, L., Zhang, D., Yang, C., \u0026amp; Wang, Y. (2018). HARNESSING SOCIAL MEDIA FOR HEALTH INFORMATION MANAGEMENT. \u003cem\u003eElectronic commerce research and applications\u003c/em\u003e, \u003cem\u003e27\u003c/em\u003e, 139–151. https://doi.org/10.1016/j.elerap.2017.12.003\u003c/li\u003e\n\u003cli\u003eFassi, L., Ferguson, A.M., Przybylski, A.K. \u003cem\u003eet al.\u003c/em\u003e Social media use in adolescents with and without mental health conditions. \u003cem\u003eNat Hum Behav\u003c/em\u003e 9, 1283–1299 (2025). https://doi.org/10.1038/s41562-025-02134-4\u003c/li\u003e\n\u003cli\u003eGhahramani, A., de Courten, M. \u0026amp; Prokofieva, M. “The potential of social media in health promotion beyond creating awareness: an integrative review”. \u003cem\u003eBMC Public Health\u003c/em\u003e 22, 2402 (2022). https://doi.org/10.1186/s12889-022-14885-0\u003c/li\u003e\n\u003cli\u003eKanchan, S., \u0026amp; Gaidhane, A. (2023). Social Media Role and Its Impact on Public Health: A Narrative Review. \u003cem\u003eCureus\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(1), e33737. https://doi.org/10.7759/cureus.33737\u003c/li\u003e\n\u003cli\u003eSärnholm, J., \u0026amp; Kronish, I. M. (2024). Psychological Distress and Hypertension Diagnostic Testing: Is There Anything to Worry About?. \u003cem\u003eAmerican journal of hypertension\u003c/em\u003e, \u003cem\u003e37\u003c/em\u003e(1), 18–20. https://doi.org/10.1093/ajh/hpad096\u003c/li\u003e\n\u003cli\u003eAlwani, A. A., Singh, U., Sankhyan, S., Chandra, A., Rai, S. K., \u0026amp; Nongkynrih, B. (2023). Hypertension-related distress and its associated factors: findings from an urban primary health centre of South Delhi, India. \u003cem\u003eJournal of family medicine and primary care\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(9), 1885–1892. https://doi.org/10.4103/jfmpc.jfmpc_1909_22\u003c/li\u003e\n\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":"Hypertension, Social Media, Patient Experience, Sentiment Analysis, Twitter, Reddit","lastPublishedDoi":"10.21203/rs.3.rs-7971307/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7971307/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e\u003cp\u003eHypertension a prominent cardiovascular condition with significant burden on healthcare around the globe. Literary research methods often unwillingly ignore real-world patient experiences and emotional responses. Social media platforms, such as Twitter/X and Reddit, offer a unique and realistic opportunity to study patient perceptions and behavior regarding hypertension in a more naturalistic and unbiased setting.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePosts which were publicly available were collected from Twitter/X and Reddit subreddits(n\u0026thinsp;=\u0026thinsp;1 070) which primarily focused on hypertension. Posts were cleaned, anonymized, and analyzed for keyword mentions (\u0026ldquo;\u003cem\u003ehigh BP\u003c/em\u003e,\u0026rdquo; \u0026ldquo;\u003cem\u003ehypertension\u003c/em\u003e,\u0026rdquo; \u0026ldquo;\u003cem\u003eblood pressure\u003c/em\u003e,\u0026rdquo; \u0026ldquo;\u003cem\u003emedication\u003c/em\u003e\u0026rdquo;) and sentiment (Positive, Neutral, Negative) using Python and TextBlob. Descriptive statistics, including sentiment and keyword frequency, were generated.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe data (n\u0026thinsp;=\u0026thinsp;1 070 posts) included 46.7% Neutral, 34.6% Positive, and 18.7% Negative posts. Keyword analysis showed \u0026ldquo;\u003cem\u003ehypertension\u003c/em\u003e\u0026rdquo; (1 570 mentions) as the most common, followed by \u0026ldquo;\u003cem\u003eblood pressure\u003c/em\u003e\u0026rdquo; (630), \u0026ldquo;\u003cem\u003emedication\u003c/em\u003e\u0026rdquo; (260), and \u0026ldquo;\u003cem\u003ehigh BP\u003c/em\u003e\u0026rdquo; (140). Positive posts mostly were focused on describing lifestyle interventions or successfully controlled blood pressure, while Negative posts majorly highlighted anxiety, side effects, or frequent BP spikes.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSocial media provides an insightful lens into real-world experiences of individuals with hypertension, capturing both factual and emotional dimensions. Publicly available dataset on social media allow for more robust analysis, and these insights can inform public health strategies, patient education, and clinical awareness. Social media may serve as a companion tool to researchers and physicians, offering timely, patient-centered perspectives.\u003c/p\u003e","manuscriptTitle":"Exploring Public Perceptions and Experiences of Hypertension Through Social Media: Insights from Twitter/X and Reddit","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-18 16:43:41","doi":"10.21203/rs.3.rs-7971307/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":"5c15e933-e5f7-497f-9afa-85907621eed2","owner":[],"postedDate":"November 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57758457,"name":"Health sciences/Medical research"},{"id":57758458,"name":"Health sciences/Health care/Prognosis"},{"id":57758459,"name":"Health sciences/Diseases/Cardiovascular diseases/Hypertension"}],"tags":[],"updatedAt":"2025-12-02T04:43:44+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-18 16:43:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7971307","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7971307","identity":"rs-7971307","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}