Explorando o impacto das hashtags virais no comportamento de busca de informações sobre saúde online:
insights de uma pesquisa com estudantes
Palavras-chave:
Alfabetização digital, Comportamentos de saúde, Mídias sociais, Tendências, Engajamento do usuárioResumo
Este estudo explora o impacto de tendências e de conteúdo viral no comportamento de busca de informações sobre saúde online, com foco em como os usuários interagem e avaliam informações digitais sobre saúde. O objetivo é examinar o papel das tendências online emergentes na formação de percepções e na tomada de decisões sobre informações sobre saúde. Uma pesquisa transversal foi conduzida na Universidad Carlos III de Madri em maio de 2023, envolvendo 107 participantes recrutados por amostragem de conveniência. O instrumento da pesquisa, administrado via Google Forms, consistia em perguntas estruturadas para avaliar a exposição ao conteúdo viral sobre saúde, sua credibilidade percebida e sua influência em ações relacionadas à saúde. Os dados foram analisados usando estatísticas descritivas e inferenciais para identificar padrões e correlações. Os resultados revelam que uma proporção significativa de participantes depende de tendências de mídia social para informar suas decisões sobre saúde, com o conteúdo viral frequentemente percebido como confiável com base na popularidade, ao invés da confiabilidade da fonte. No entanto, o estudo também destaca disparidades na alfabetização digital, com alguns participantes demonstrando capacidade limitada para avaliar criticamente informações sobre saúde online. Essas descobertas ressaltam a necessidade de intervenções direcionadas a fim de aprimorar a capacidade dos usuários de navegar e avaliar informações de saúde na era digital. O estudo contribui para a compreensão da intersecção de tendências digitais e comportamentos de saúde, oferecendo insights para pesquisas futuras e estratégias de saúde pública voltadas à promoção da tomada de decisão informada no contexto de crescente dependência de plataformas online.
Downloads
Referências
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.
Downloads
Publicado
Como Citar
Edição
Seção
Licença
Copyright (c) 2025 Transinformação
Este trabalho está licenciado sob uma licença Creative Commons Attribution 4.0 International License.
