Exploring the impact of viral hashtags on online health information-seeking behavior:
insights from a student survey
Keywords:
Digital literacy, Health behaviors, Social media, Trends, User engagementAbstract
This study explores the impact of trends and viral content on online health informationseeking behavior, focusing on how users interact with and evaluate digital health information. The objective is to examine the role of emerging online trends in shaping perceptions and decision-making regarding health information. A cross-sectional survey was conducted at the Universidad Carlos III de Madrid in May 2023, involving 107 participants recruited through convenience sampling. The survey instrument, administered via Google Forms, consisted of structured questions assessing exposure to viral health content, participants’ perceptions of its credibility, and its influence on health-related actions. The data was analyzed using descriptive and inferential statistics to identify patterns and correlations. Results reveal that a considerable proportion of participants rely on social media trends to inform their health decisions, with viral content often perceived as credible based on popularity rather than source reliability. However, the study also highlights disparities in digital literacy, with some participants demonstrating limited ability to critically evaluate online health information. These findings underscore the need for targeted interventions to enhance users’ ability to navigate and assess health information in the digital age. The study contributes to understanding the intersection of digital trends and health behaviors, offering insights into future research and public health strategies aimed at promoting informed decision-making in the context of increasing reliance on online platforms.
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References
Aboulhosn, S. Twitter trending topics: How they work and how to use them. Sprout Social, March 15, 2021. Available from: https://sproutsocial.com/insights/twitter-trending-topics/. Cited: 11 nov. 2025.
Agam, D. The impact of viral marketing through Instagram. Australasian Journal of Business, Social Science and Information Technology, v. 4, n. 1, 2017.
Ali, K. et al. Viruses going viral: impact of fear-arousing sensationalist social media messages on user engagement. Science Communication, v. 41, n. 3, p. 314-338, 2019. Doi: https://doi.org/10.1177/1075547019846124.
Andry, J. F. et al. Algorithm of trending videos on YouTube analysis using classification, association and clustering. Proceedings of the International Conference on Data and Software Engineering (ICoDSE). Bandung: IEEE, 2021. Doi: https://doi.org/10.1109/ICoDSE53690.2021.9648486.
Anthonysamy, L.; Sivakumar, P. A new digital literacy framework to mitigate misinformation in social media infodemic. Global Knowledge, Memory and Communication, v. 73, n. 6/7, p. 809-827, 2024. Doi: https://doi.org/10.1108/GKMC-06-2022-0142.
Arias López, M. d.-P.A. et al. Digital literacy as a new determinant of health: a scoping review. Plos Digital Health, v. 2, n. 10, e0000279, 2023. Doi: https://doi.org/10.1371/journal.pdig.0000279.
Arom, D. Twitter and viral trends. SocArXiv, v.1, 2018. Doi: https://doi.org/10.31235/osf.io/8numc.
Astari, N. A literature review: digital marketing trends in Indonesia during the COVID-19 pandemic. Channel: Jurnal Komunikasi, v. 9, n. 2, p. 125, 2021. Doi: https://doi.org/10.12928/channel.v9i2.20836.
Asur, S. et al. Trends in social media:persistence and decay. Proceedings of the International AAAI. Conference on Web and Social Media, v. 5, n. 1, 2011. Doi: https://doi.org/10.1609/icwsm.v5i1.14167.
Bak, C.K. et al. Digital health literacy and information-seeking behavior among university college students during the COVID-19 pandemic: a cross-sectional study from Denmark. International Journal of Environmental Research and Public Health, v. 19, n. 6, e3676, 2022. Doi: https://doi.org/10.3390/ijerph19063676.
Barbe, D.; Neuburger, L. Generation Z and digital influencers in the tourism industry. In: Stylos, N. et al. (org.). Generation Z Marketing and Management in Tourism and Hospitality: The Future of the Industry. Cham: Springer International Publishing, 2021. p. 167-192. Doi: https://doi.org/10.1007/978-3-030-70695-1_7.
Bautista, J.R.; Zhang, Y.; Gwizdka, J. Healthcare professionals’ acts of correcting health misinformation on social media. International Journal of Medical Informatics, v. 148, e104375, 2021. Doi: https://doi.org/10.1016/j.ijmedinf.2021.104375.
Blechschmidt, J. Trend management: how to effectively use trend-knowledge in your company. [S. l.]: Springer, 2022.
Bowen, J. Trends affecting social media: Implications for practitioners and researchers. Worldwide Hospitality and Tourism Themes, v. 7, n. 3, 221-228, 2015. Doi: https://doi.org/10.1108/WHATT-04-2015-0021.
Broniatowski, D. A. et al. health communication: Twitter bots and Russian trolls amplify the vaccine debate. American Journal of Public Health, v. 108, n. 10, p. 1378-1384, 2018. Doi: https://doi.org/10.2105/AJPH.2018.304567.
Chan, M.S. et al. Debunking: a meta-analysis of the psychological efficacy of messages countering misinformation. Psychological Science, v. 28, n. 11, p. 1531-1546, 2017. Doi: https://doi.org/10.1177/0956797617714579.
Cheong, M. What are you tweeting about?’: a survey of trending topics within Twitter. [S. l.: s. n.], 2009. Available from: https://scholar.archive.org/work/26z5zg5ndzctnhbk7gdmosgghy/access/wayback/https://aueast.erc.monash.edu.au/fpfiles/36404382/tr2009251full.pdf?AWSAccessKeyId=e00145a6f706457aab45 051570081e49&Expires=1658824855&Signature=eCGpJRJJQWBNgY%2B%2BeN1FWdRE5uA%3D. Cited: Mar. 3, 2024.
Chew, C.; Eysenbach, G. Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak. Plos One, v. 5, n. 11, e14118, 2010. Doi: https://doi.org/10.1371/journal.pone.0014118.
Dadaczynski, K.; Okan, O.; Rathmann, K. COVID-19 Health Literacy Survey: university students (COVIDHL-Survey). Questionnaire and Scale Documentation. Version 1. Bielefeld/Fulda: Bielefeld University, Interdisciplinary Centre for Health Literacy Research and Fulda University of Applied Sciences, Public Health Centre, 2020. Doi: https://doi.org/10.4119/unibi/2942920.
Dăniasă, C.I. et al. The mechanisms of the influence of viral marketing in social media. Economics, Management & Financial Markets, v. 5, n. 3, p. 278-282, 2010.
Deng, Z.; Liu, S. Understanding consumer health information-seeking behavior from the perspective of the risk perception attitude framework and social support in mobile social media websites. International Journal of Medical Informatics, v. 105, p. 98-109, 2017. Doi: https://doi.org/10.1016/j.ijmedinf.2017.05.014.
Dharawat, A.R. et al. Drink bleach or do what now? Covid-HeRA: a dataset for risk-informed health decision making in the presence of COVID19 misinformation. ACL, 2020. Available from: https://openreview.net/forum?id=PmY1SNmJlEC. Cited: Mar. 3, 2024.
Diepeveen, S.; Pinet, M. User perspectives on digital literacy as a response to misinformation. Development Policy Review, v. 10, n. 52, e12671, 2022. Doi: https://doi.org/10.1111/dpr.12671.
Download Data | HINTS. [S. l.]: NIH. Available from: https://hints.cancer.gov/data/download-data.aspx#H5C4. Cited: Feb. 15, 2023.
Eshet, Y. Digital literacy: a Conceptual framework for survival skills in the Digital Era. Journal of Educational Multimedia and Hypermedia, v. 13, n. 1, p. 93-106, 2004.
Fernandez, M.; Alani, H. Online misinformation: Challenges and future directions. In: International World Wide Web Conference, 18., 2018, Lyon. Proceedings [...]. Lyon, 2018. p. 595-602. Doi: https://doi.org/10.1145/3184558.3188730.
Fernández-Luque, L.; Bau, T. Health and social media: perfect storm of information. Healthcare Informatics Research, v. 21, n. 2, p. 67-73, 2015. Doi: https://doi.org/10.4258/hir.2015.21.2.67.
Gottfried, J. Americans’ social media use. Pew Research Center, January 31, 2024. Available from: https://www.pewresearch.org/internet/2024/01/31/americans-social-media-use/. Cited: 11 nov. 2025.
Hamid, S. et al. Role of social media in information-seeking behaviour of international students: a systematic literature review. Aslib Journal of Information Management, v. 68, n. 5, p. 643-666, 2016. Doi: https://doi.org/10.1108/AJIM-03-2016-0031.
Himelboim, I.; Han, J.Y. Cancer talk on Twitter: community structure and information sources in breast and prostate cancer social networks. Journal of Health Communication, v. 19, n. 2, p. 210-225, 2014. Doi: https://doi.org/10.1080/10810730.2013.811321.
Howarth, J. TikTok user age, gender, & demographics. Exploding Topics, January 12, 2024. Avaiable from: https://explodingtopics.com/blog/tiktok-demographics. Cited: 11 nov. 2025.
Internet and social media users in the world 2024. Statista, 2024. Available from: https://www.statista.com/statistics/617136/digital-population-worldwide/. Cited: Mar. 2, 2024.
Jia, X.; Pang, Y.; Liu, L.S. Online health information seeking behavior: a systematic review. Healthcare, v. 9, n. 12, 2021. Doi: https://doi.org/10.3390/healthcare9121740.
Jones, S. L.; Hadjistavropoulos, H.D.; Gullickson, K. Understanding health anxiety following breast cancer diagnosis. Psychology, Health & Medicine, v. 19, n. 5, p. 525-535, 2014. Doi: https://doi.org/10.1080/13548506. 2013.845300.
Jung, M. Determinants of health information-seeking behavior: implications for post-treatment cancer patients. Asian Pacific Journal of Cancer Prevention: APJCP, v. 15, n. 16, p. 6499-6504, 2014. Doi: https://doi.org/10.7314/apjcp.2014.15.16.6499.
Kamble, S. How different generations use social media. Feedough, July 28, 2023. Available from: https://www.feedough.com/how-different-generations-use-social-media/. Cited: 11 nov. 2025.
Kamel Boulos, M. N.; Wheeler, S. The emerging Web 2.0 social software: an enabling suite of sociable technologies in health and health care education. Health Information and Libraries Journal, v. 24, n. 1, p. 2-23, 2007. Doi: https://doi.org/10.1111/j.1471-1842.2007.00701.x.
Katz, M.S. et al. Organizing online health content: developing hashtag collections for healthier internet-based people and communities. JCO Clinical Cancer Informatics, v. 3, p. 1-10, 2019. Doi: https://doi.org/10.1200/CCI.18.00124.
Kennedy, S.; Yaldren, J. A look at digital literacy in health and social care. British Journal of Cardiac Nursing, v. 12, n. 9, p. 428-432, 2017. Doi: https://doi.org/10.12968/bjca.2017.12.9.428.
Kim, H.S. Attracting views and going viral: how message features and news-sharing channels affect health news diffusion. Journal of Communication, v. 65, n. 3, p. 512-534, 2015.
Klug, D. et al. Trick and please: a mixed-method study on user assumptions about the TikTok algorithm. In: 13th ACM Web Science Conference, 13., 2021, Braunschweing. Proceedings [...]. Braunschweing, 2021. p. 84-92, 2021. Doi: https://doi.org/10.1145/3447535.3462512.
Korbani, A.; LaBrie, J. Toxic TikTok trends. Journal of Student Research, v. 10, n. 2, 2021.
Kouzy, R. et al. Coronavirus goes viral: quantifying the COVID-19 misinformation epidemic on Twitter. Cureus, v. 12, n. 3, 2020.
Kriegel, E. R. et al. TikTok, Tide Pods and Tiger King: health implications of trends taking over pediatric populations. Current Opinion in Pediatrics, v. 33, n. 1, p. 170-177, 2021.
Krishna, A.; Zambreno, J.; Krishnan, S. Polarity trend analysis of public sentiment on YouTube. In: International Conference on Management of Data, 19., 2013, Mumbai. Proceedings [...]. Mumbai: ACM, 2013. p. 125-128. Doi: https://dl.acm.org/doi/book/10.5555/2694476.
Lagoe, C.; Atkin, D. Health anxiety in the digital age: an exploration of psychological determinants of online health information seeking. Computers in Human Behavior, v. 52, p. 484-491, 2015. Doi: https://doi.org/10.1016/j.chb.2015.06.003.
Laranjo, L. et al. The influence of social networking sites on health behavior change: a systematic review and meta-analysis. Journal of the American Medical Informatics Association, v. 22, n. 1, p. 243-256, 2015. Doi: https://doi.org/10.1136/amiajnl-2014-002841.
Larson, R. The rise of viral marketing through the new media of social media. Faculty Publications and Presentations, v. 6, 2009.
Latkin, C.A.; Knowlton, A.R. Social network assessments and interventions for health behavior change: a critical review. Behavioral Medicine, v. 41, n. 3, p. 90-97, 2015. Doi: https://doi.org/10.1080/08964289.2015.1034645.
Lee, D.K.L.; Ramazan, O. Fact-checking of health information: the effect of media literacy, metacognition and health information exposure. Journal of Health Communication, v. 26, n. 7, p. 491-500, 2021. Doi: https://doi.org/10.1080/10810730.2021.1955312.
Lee, H.Y. et al. Role of health literacy in health-related information-seeking behavior online: cross-sectional study. Journal of Medical Internet Research, v. 23, n. 1, e14088, 2021. Doi: https://doi.org/10.2196/14088.
Lee, Y.J. et al. Predictors of health information-seeking behaviors in Hispanics. In: International Congress on Nursing Informatics, 11., 2012, Montreal. Proceedings [...]. Montreal: IEEE, 2012.
Li, H.; Sakamoto, Y. Computing the veracity of information through crowds: a method for reducing the spread of false messages on social media. In: Hawaii International Conference on System Sciences, 48., 2015, Kauai. Proceedings [...]. Kauai: IEEE, 2015. p. 2003-2012. Doi: https://doi.org/10.1109/HICSS.2015.240.
Li, J.; Theng, Y.-L.; Foo, S. Predictors of online health information seeking behavior: changes between 2002 and 2012. Health Informatics Journal, v. 22, n. 4, p. 804-814, 2016. Doi: https://doi.org/10.1177/1460458215595851.
Lim, M.S.C. et al. Young adults’ use of different social media platforms for health information: insights from web-based conversations. Journal of Medical Internet Research, v. 24, n. 1, e23656, 2022. Doi: https://doi.org/10.2196/23656.
Loeb, S. et al. Dissemination of misinformative and biased information about prostate cancer on YouTube. European Urology, v. 75, n. 4, p. 564-567, 2019. Doi: https://doi.org/10.1016/j.eururo.2018.10.056.
Ma, Z.; Sun, A.; Cong, G. Will this #hashtag be popular tomorrow? In: International ACM SIGIR Conference on Research and Development in Information Retrieval, 35., Portland, 2012. Proceedings [...]. Portland: ACM, 2012. p. 1173-1174. Doi: https://doi.org/10.1145/2348283.2348525.
Morahan-Martin, J.M. How internet users find, evaluate, and use online health information: A cross-cultural review. Cyberpsychology & Behavior: The Impact of the Internet, Multimedia and Virtual Reality on Behavior and Society, v. 7, n. 5, p. 497-510, 2004. Doi: https://doi.org/10.1089/cpb.2004.7.497.
Myrick, J.G. The role of emotions and social cognitive variables in online health information seeking processes and effects. Computers in Human Behavior, v. 68, p. 422-433, 2017. Doi: https://doi.org/10.1016/j.chb.2016.11.071.
Naaman, M.; Becker, H.; Gravano, L. Hip and trendy: characterizing emerging trends on Twitter. Journal of the American Society for Information Science and Technology, v. 62, n. 5, p. 902-918, 2011. Doi: https://doi.org/10.1002/asi.21489.
Nahon, K.; Hemsley, J. Going viral. Cambridge: Polity, 2013.
Neely, S.; Eldredge, C.; Sanders, R. Health information seeking behaviors on social media during the COVID-19 pandemic among American social networking site users: Survey study. Journal of Medical Internet Research, v. 23, n. 6, e29802, 2021. Doi: https://doi.org/10.2196/29802.
Noh, Y. A study on the effect of digital literacy on information use behavior. Journal of Librarianship and Information Science, v. 49, n. 1, 2016. Doi: https://doi.org/10.1177/09610006156245.
Okoro, Y.O. et al. A review of health misinformation on digital platforms: challenges and countermeasures. International Journal of Applied Research in Social Sciences, v. 6, n. 1, 2024. Doi: https://doi.org/10.51594/ijarss.v6i1.689.
Osop, H. et al. (2020). Diabetweets: Analysis of Tweets for Health-Related Information. In: Stephanidis,C.; Antona, M.; Ntoa, S. (ed.). HCI International 2020 – Late Breaking Posters. [S. l.]: Springer International Publishing, 2020. p. 500-508. Doi: https://doi.org/10.1007/978-3-030-60703-6_65.
Paek, H.-J.; Hove, T. Determinants of vertical and horizontal online health information behavior. In: Hawaii International Conference on System Sciences, 47., 2014, Waikoloa. Proceedings [...]. Waikoloa: IEEEp. 2597-2606, 2014. Doi: https://doi.org/10.1109/HICSS.2014.328.
Pallis, G.; Zeinalipour-Yazti, D.; Dikaiakos, M.D. Online social networks: status and trends. In: Vakali, A.; Jain, L.C. (ed.). New directions in web data management 1. Berlin: Springer, 2011. p. 213-234. Doi: https://doi.org/10.1007/978-3-642-17551-0_8.
Polizzi, G.; Taylor, R. Misinformation, digital literacy and the school curriculum. London: London School of Economics and Political Science, 2019. Available from: https://blogs.lse.ac.uk/mediapolicyproject/policybriefs/. Cited: Sep. 28, 2024.
Prier, J. Commanding the trend: Social media as information warfare. Strategic Studies Quarterly, v. 11, n. 4, p. 50-85, 2017.
Purba, K.R.; Asirvatham, D.; Murugesan, R.K. Instagram post popularity trend analysis and prediction using hashtag, image assessment, and user history features. International Arab Journal of Information Technology, v. 18, n. 1, p. 85-94, 2021.
Reed, C.; Elvers, T.; Srinivasan, P. What’s trending? Mining topical trends in UGC systems with YouTube as a case study. In: International Workshop on Multimedia Data Mining, 11., 2011, San Diego. Proceedings [...]. San Diego: ACM, 2011. p. 1-9. Doi: https://doi.org/10.1145/2237827.2237831.
Rice, R. E. Influences, usage, and outcomes of Internet health information searching: multivariate results from the Pew surveys. International Journal of Medical Informatics, v. 75, n. 1, p. 8-28, 2006. Doi: https://doi.org/10.1016/j.ijmedinf.2005.07.032.
Sajid, S.I. Social media and its role in marketing. Business and Economics Journal, v. 7, n. 1, p. 203207, 2016.
Sakaki, T.; Okazaki, M.; Matsuo, Y. Earthquake shakes Twitter users: real-time event detection by social sensors. In: International Conference on World Wide Web, 10., 2010, New York. Proceedings [...]. New York: ACM, 2010. p. 851-860. Doi: https://doi.org/10.1145/1772690.1772777.
Sankaranarayanan, J. et al. TwitterStand: news in tweets. ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 17., 2009, Seattle Washington. Proceedings [...]. Seattle Washington: ACM, 2009. p. 42-51. Doi: https://doi.org/10.1145/1653771.1653781.
Sanz Suárez-Lledó, V.J.; Álvarez Gálvez, J. Prevalence of health misinformation on social media: systematic review. Journal of Medical Internet Research, v. 23, n. 1, e17187, 2021. Doi: https://doi.org/10.2196/17187.
Schäfer, M. et al. Health information seeking among university students before and during the corona crisis— findings from Germany. Frontiers in Public Health, v. 8, 2021. Doi: https://doi.org/10.3389/fpubh.2020.616603.
Schuetz, S.W.; Sykes, T. A.; Venkatesh, V. Combating COVID-19 fake news on social media through fact checking: antecedents and consequences. European Journal of Information Systems, v. 30, n. 4, p. 376-388, 2021. Doi: https://doi.org/10.1080/0960085X.2021.1895682.
Social Media by Generation. [S. l.]: GWI, 2023. Available from: https://www.gwi.com/reports/social-mediause-by-generation. Cited: Mar. 6, 2024.
Sokolova, K.; Kefi, H. Instagram and YouTube bloggers promote it, why should I buy? How credibility and parasocial interaction influence purchase intentions. Journal of Retailing and Consumer Services, v. 53, 101742, 2020. Doi: https://doi.org/10.1016/j.jretconser.2019.01.011.
Soroya, S.H. et al. From information seeking to information avoidance: understanding the health information behavior during a global health crisis. Information Processing & Management, v. 58, n. 2, 102440, 2021. Doi: https://doi.org/10.1016/j.ipm.2020.102440.
Spezi, V. Is information-seeking behavior of doctoral students changing? A review of the literature (2010– 2015). New Review of Academic Librarianship, v. 22, n. 1, p. 78-106, 2016. Doi: https://doi.org/10.1080/13614533.2015.1127831.
St Claire, K.M. et al. Dermatology on YouTube—an update and analysis of new trends. Dermatology Online Journal, v. 24, n. 12, 2018.
Statistica. Instagram: Age distribution of global audiences 2024. Statista, 2024. Available from: https://www.statista.com/statistics/325587/instagram-global-age-group/. Cited: Nov. 13, 2025.
Suwana, F. et al. Digital media use of Gen Z during COVID-19 pandemic. Jurnal Sosioteknologi, v. 19, n. 3, p. 327-340, 2020.
Szeto, M.D. et al. Social media in dermatology and an overview of popular social media platforms. Current Dermatology Reports, v. 10, n. 4, p. 97-104, 2021. Doi: https://doi.org/10.1007/s13671-021-00343-4.
Tsur, O.; Rappoport, A. What’s in a hashtag? Content-based prediction of the spread of ideas in microblogging communities. In: ACM International Conference on Web Search and Data Mining, 5., 2012, Seattle Washington. Proceedings [...]. Seattle Washington: ACM, 2012. p. 643-652. Doi: https://doi.org/10.1145/2124295.2124320.
Twitter trends FAQ – trending hashtags and topics. [S. l.], c2025. Available from: https://help.twitter.com/en/using-twitter/twitter-trending-faqs. Cited: Mar. 4, 2024.
Varol, O. et al. Early detection of promoted campaigns on social media. EPJ Data Science, v. 6, n. 1, p. 13, 2017. Doi: https://doi.org/10.1140/epjds/s13688-017-0111-y.
Vijay, V. et al. Using internet search data to understand information seeking behavior for health and conservation topics during the COVID-19 pandemic. Biological Conservation, v. 257, 109078, 2021. Doi: https://doi.org/10.1016/j.biocon.2021.109078.
Wang, X. et al. What makes cancer information viral on social media? Computers in Human Behavior, v. 93, p. 149-156, 2019b. Doi: https://doi.org/10.1016/j.chb.2018.12.024.
Wang, Y. et al. Systematic literature review on the spread of health-related misinformation on social media. Social Science & Medicine, v. 240, 112552, 2019a. Doi: https://doi.org/10.1016/j.socscimed.2019.112552.
YouTube Age Demographics [Updated Feb 2023]. Oberlo, c2015-2025. Available from: https://www.oberlo.com/statistics/youtube age-demographics. Cited: Mar. 9, 2024.
Zhang, J. et al. Effects of fact-checking social media vaccine misinformation on attitudes toward vaccines. Preventive Medicine, v. 145, 106408, 2021. Doi: https://doi.org/10.1016/j.ypmed.2020.106408.
Zhao, Y.; Zhang, J. Consumer health information seeking in social media: A literature review. Health Information & Libraries Journal, v. 34, n. 4, p. 268-283, 2017. Doi: https://doi.org/10.1111/hir.12192.
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