ABSTRACT
Obesity and diabetes epidemics are affecting about a third and tenth of US population, respectively, capturing the attention of the nation and its institutions. Social media provides an open forum for communication between individuals and health organizations, a forum which is easily joined by parties seeking to gain profit from it. In this paper we examine 1.5 million tweets mentioning obesity and diabetes in order to assess (1) the quality of information circulating in this conversation, as well as (2) the behavior and information needs of the users engaged in it. The analysis of top cited domains shows a strong presence of health information sources which are not affiliated with a governmental or academic institution at 41% in obesity and 50% diabetes samples, and that tweets containing these domains are retweeted more than those containing domains of reputable sources. On the user side, we estimate over a quarter of non-informational obesity discourse to contain fat-shaming -- a practice of humiliating and criticizing overweight individuals -- with some self-directed toward the writers themselves. We also find a great diversity in questions asked in these datasets, spanning definition of obesity as a disease, social norms, and governmental policies. Our results indicate a need for addressing the quality control of health information on social media, as well as a need to engage in a topically diverse, psychologically charged discourse around these diseases.
- Ahmed Abbasi, Tianjun Fu, Daniel Zeng, and Donald Adjeroh. 2013. Crawling credible online medical sentiments for social intelligence Social Computing (SocialCom), 2013 International Conference on. IEEE, 254--263. Google ScholarDigital Library
- Samantha A Adams. 2010. Revisiting the online health information reliability debate in the wake of “web 2.0”: an inter-disciplinary literature and website review. International journal of medical informatics Vol. 79, 6 (2010), 391--400.Google Scholar
- Sharon E Alajajian, Jake Ryland Williams, Andrew J Reagan, Stephen C Alajajian, Morgan R Frank, Lewis Mitchell, Jacob Lahne, Christopher M Danforth, and Peter Sheridan Dodds. 2018. The Lexicocalorimeter: Gauging public health through caloric input and output on social media. PloS one Vol. 12, 2 (2018), e0168893.Google Scholar
- Susan H Babey, Allison L Diamant, Theresa A Hastert, Stefan Harvey, et almbox.. 2008. Designed for disease: the link between local food environments and obesity and diabetes. UCLA Center for Health Policy Research (2008).Google Scholar
- Gretchen K Berland, Marc N Elliott, Leo S Morales, Jeffrey I Algazy, Richard L Kravitz, Michael S Broder, David E Kanouse, Jorge A Mu noz, Juan-Antonio Puyol, Marielena Lara, et almbox.. 2001. Health information on the Internet: accessibility, quality, and readability in English and Spanish. Jama Vol. 285, 20 (2001), 2612--2621.Google ScholarCross Ref
- Elmer V Bernstam, Muhammad F Walji, Smitha Sagaram, Deepak Sagaram, Craig W Johnson, and Funda Meric-Bernstam. 2008. Commonly cited website quality criteria are not effective at identifying inaccurate online information about breast cancer. Cancer Vol. 112, 6 (2008), 1206--1213.Google ScholarCross Ref
- Rowena Briones, Xiaoli Nan, Kelly Madden, and Leah Waks. 2012. When vaccines go viral: an analysis of HPV vaccine coverage on YouTube. Health communication Vol. 27, 5 (2012), 478--485.Google Scholar
- CDC. 2018. National Diabetes Statistics Report, 2018. National Center for Chronic Disease Prevention and Health Promotion (2018).Google Scholar
- Cynthia Chew and Gunther Eysenbach. 2010. Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak. PloS one Vol. 5, 11 (2010), e14118.Google ScholarCross Ref
- Wen-ying Sylvia Chou, Abby Prestin, and Stephen Kunath. 2014. Obesity in social media: a mixed methods analysis. Translational behavioral medicine Vol. 4, 3 (2014), 314--323.Google Scholar
- Giovanni Luca Ciampaglia, Prashant Shiralkar, Luis M Rocha, Johan Bollen, Filippo Menczer, and Alessandro Flammini. 2015. Computational fact checking from knowledge networks. PloS one Vol. 10, 6 (2015), e0128193.Google ScholarCross Ref
- Rebecca JW Cline and Katie M Haynes. 2001. Consumer health information seeking on the Internet: the state of the art. Health education research Vol. 16, 6 (2001), 671--692.Google Scholar
- Adam G Dunn, Julie Leask, Xujuan Zhou, Kenneth D Mandl, and Enrico Coiera. 2015. Associations between exposure to and expression of negative opinions about human papillomavirus vaccines on social media: an observational study. Journal of medical Internet research Vol. 17, 6 (2015).Google ScholarCross Ref
- Kristina Elfhag and Stephan Rössner. 2005. Who succeeds in maintaining weight loss? A conceptual review of factors associated with weight loss maintenance and weight regain. Obesity reviews Vol. 6, 1 (2005), 67--85.Google Scholar
- Gunther Eysenbach, John Powell, Oliver Kuss, and Eun-Ryoung Sa. 2002. Empirical studies assessing the quality of health information for consumers on the world wide web: a systematic review. Jama Vol. 287, 20 (2002), 2691--2700.Google ScholarCross Ref
- Jasmine Fardouly, Phillippa C Diedrichs, Lenny R Vartanian, and Emma Halliwell. 2015. Social comparisons on social media: The impact of Facebook on young women's body image concerns and mood. Body Image Vol. 13 (2015), 38--45.Google ScholarCross Ref
- David M Garner. 1997. The 1997 body image survey results. Psychology today Vol. 30, 1 (1997), 30--44.Google Scholar
- Amira Ghenai and Yelena Mejova. 2018. Catching Zika fever: Application of crowdsourcing and machine learning for tracking health misinformation on Twitter. International Conference on Healthcare Informatics (ICHI) (2018).Google Scholar
- Jeremy A Greene, Niteesh K Choudhry, Elaine Kilabuk, and William H Shrank. 2011. Online social networking by patients with diabetes: a qualitative evaluation of communication with Facebook. Journal of general internal medicine Vol. 26, 3 (2011), 287--292.Google ScholarCross Ref
- Craig Hales, Margaret Carroll, Cheryl D. Fryar, and Cynthia L. Ogden. 2016. Prevalence of Obesity Among Adults and Youth: United States, 2015--2016. Centers for Disease Control and Prevention. National Center for Health Statistics (2016).Google Scholar
- Jennifer Hansen. 2014. Explode and die! A fat woman's perspective on prenatal care and the fat panic epidemic. Narrative inquiry in bioethics Vol. 4, 2 (2014), 99--101.Google Scholar
- Jenine K Harris, Alexis Duncan, Vera Men, Nora Shevick, Melissa J Krauss, and Patricia A Cavazos-Rehg. 2018. Peer Reviewed: Messengers and Messages for Tweets That Used# thinspo and# fitspo Hashtags in 2016. Preventing chronic disease Vol. 15 (2018).Google Scholar
- Maximilian Jenders, Gjergji Kasneci, and Felix Naumann. 2013. Analyzing and predicting viral tweets. In Proceedings of the 22nd International Conference on World Wide Web. ACM, 657--664. Google ScholarDigital Library
- Venk Kandadai, Haodong Yang, Ling Jiang, Christopher C Yang, Linda Fleisher, and Flaura Koplin Winston. 2016. Measuring health information dissemination and identifying target interest communities on Twitter: methods development and case study of the@ SafetyMD network. JMIR research protocols Vol. 5, 2 (2016).Google Scholar
- Yung-Hsi Kao, Hsin-Huei Chang, Meng-Jung Lee, and Chia-Lin Chen. 2006. Tea, obesity, and diabetes. Molecular nutrition & food research Vol. 50, 2 (2006), 188--210.Google Scholar
- Taha A Kass-Hout and Hend Alhinnawi. 2013. Social media in public health. British Medical Bulletin Vol. 108, 1 (2013), 5--24.Google ScholarCross Ref
- Anna Kata. 2010. A postmodern Pandora's box: anti-vaccination misinformation on the Internet. Vaccine Vol. 28, 7 (2010), 1709--1716.Google ScholarCross Ref
- T Kyle, D Thomas, A Ivanescu, Joseph Nadglowski, and Rebecca M Puhld. 2015. Indications of Increasing Social Rejection Related to Weight Bias. ObesityWeek. Los Angeles (CA), November Vol. 2 (2015).Google Scholar
- Theodore K Kyle, Emily J Dhurandhar, and David B Allison. 2016. Regarding obesity as a disease: evolving policies and their implications. Endocrinology and Metabolism Clinics Vol. 45, 3 (2016), 511--520.Google ScholarCross Ref
- Kristen Lovejoy and Gregory D Saxton. 2012. Information, community, and action: How nonprofit organizations use social media. Journal of Computer-Mediated Communication Vol. 17, 3 (2012), 337--353. Google ScholarDigital Library
- Janet A Lydecker, Elizabeth W Cotter, Allison A Palmberg, Courtney Simpson, Melissa Kwitowski, Kelly White, and Suzanne E Mazzeo. 2016. Does this Tweet make me look fat? A content analysis of weight stigma on Twitter. Eating and Weight Disorders-Studies on Anorexia, Bulimia and Obesity Vol. 21, 2 (2016), 229--235.Google ScholarCross Ref
- Yelena Mejova, Sofiane Abbar, and Hamed Haddadi. 2016. Fetishizing Food in Digital Age:# foodporn Around the World. ICWSM. 250--258.Google Scholar
- Yelena Mejova, Hamed Haddadi, Anastasios Noulas, and Ingmar Weber. 2015. # foodporn: Obesity patterns in culinary interactions Proceedings of the 5th International Conference on Digital Health 2015. ACM, 51--58. Google ScholarDigital Library
- Cynthia L Ogden, Margaret D. Carroll, Cheryl D. Fryar, and Katherine M. Flegal. 2015. Prevalence of Obesity Among Adults and Youth: United States, 2011--2014. NCHS Data Brief 219 (2015).Google Scholar
- Hyojung Park, Bryan H Reber, and Myoung-Gi Chon. 2016. Tweeting as health communication: health organizations' use of twitter for health promotion and public engagement. Journal of health communication Vol. 21, 2 (2016), 188--198.Google ScholarCross Ref
- Andrew Pollack. 2013. A.M.A. Recognizes Obesity as a Disease. The New York Times (2013). deftempurl%http://www.nytimes.com/2013/06/19/business/ama-recognizes-obesity-as-a-disease.html'smid=pl-share tempurlGoogle Scholar
- James O. Prochaska and Carlo C. DiClemente. 2005. The Transtheoretical Approach. Handbook of psychotherapy integration (2005).Google Scholar
- Rebecca M Puhl and Kelly D Brownell. 2003. Psychosocial origins of obesity stigma: toward changing a powerful and pervasive bias. Obesity reviews Vol. 4, 4 (2003), 213--227.Google Scholar
- Barbara J Rolls and Elizabeth A Bell. 2000. Dietary approaches to the treatment of obesity. Medical Clinics of North America Vol. 84, 2 (2000), 401--418.Google ScholarCross Ref
- Amaia Salvador, Nicholas Hynes, Yusuf Aytar, Javier Marin, Ferda Ofli, Ingmar Weber, and Antonio Torralba. 2018. Learning Cross-modal Embeddings for Cooking Recipes and Food Images. Training Vol. 720 (2018), 619--508.Google Scholar
- Jane Sarasohn-Kahn. 2008. The wisdom of patients: Health care meets online social media. (2008).Google Scholar
- Megha Sharma, Kapil Yadav, Nitika Yadav, and Keith C Ferdinand. 2018. Zika virus pandemic--analysis of Facebook as a social media health information platform. American journal of infection control Vol. 45, 3 (2018), 301--302.Google Scholar
- Ryan J Shaw and Constance M Johnson. 2011. Health information seeking and social media use on the Internet among people with diabetes. Online journal of public health informatics Vol. 3, 1 (2011).Google Scholar
- Olivia Solon. 2016. In firing human editors, Facebook has lost the fight against fake news. The Guardian (2016). deftempurl%https://www.theguardian.com/technology/2016/aug/29/facebook-trending-news-editors-fake-news-stories tempurlGoogle Scholar
- Yulia A Strekalova. 2018. Health risk information engagement and amplification on social media: News about an emerging pandemic on Facebook. Health Education & Behavior Vol. 44, 2 (2018), 332--339.Google ScholarCross Ref
- Besiki Stvilia, Lorri Mon, and Yong Jeong Yi. 2009. A model for online consumer health information quality. Journal of the Association for Information Science and Technology Vol. 60, 9 (2009), 1781--1791. Google ScholarDigital Library
- Michael Tanner. 2013. Obesity is not a Disease. National Review (July. 2013). deftempurl%http://www.nationalreview.com/article/352626/obesity-not-disease-michael-tanner tempurlGoogle Scholar
- Kurt Thomas, Chris Grier, Dawn Song, and Vern Paxson. 2011. Suspended accounts in retrospect: an analysis of twitter spam Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference. ACM, 243--258. Google ScholarDigital Library
- J. Kevin Thomson and Lauren Schaefer. 2018. Body Image, Obesity, and Eating Disorders. Eating Disorders and Obesity: A Comprehensive Handbook (2018), 140.Google Scholar
- Anne-Marie Tomchak. 2018. Algorithms are screwing us over with fake news but could also fix the problem. Mashable (2018). deftempurl%https://mashable.com/2018/10/05/artificial-intelligence-algorithm-neva-labs/#iQuXMaJJeaqU tempurlGoogle Scholar
- Amar Toor. 2016. Reuters built an algorithm to flag and verify breaking news on Twitter. The Verge (2016). deftempurl%https://www.theverge.com/2016/12/1/13804542/reuters-algorithm-breaking-news-twitter tempurlGoogle Scholar
- Emily K Vraga and Leticia Bode. 2018. I do not believe you: how providing a source corrects health misperceptions across social media platforms. Information, Communication & Society (2018), 1--17.Google Scholar
- Leila Weitzel, José Palazzo M de Oliveira, and Paulo Quaresma. 2014. Measuring the reputation in user-generated-content systems based on health information. Procedia Computer Science Vol. 29 (2014), 364--378.Google ScholarCross Ref
- Elad Yom-Tov and Luis Fernandez-Luque. 2014. Information is in the eye of the beholder: Seeking information on the MMR vaccine through an Internet search engine. In AMIA Annual Symposium Proceedings, Vol. Vol. 2014. American Medical Informatics Association, 1238.Google Scholar
- Elad Yom-Tov, Luis Fernandez-Luque, Ingmar Weber, and Steven P Crain. 2012. Pro-anorexia and pro-recovery photo sharing: a tale of two warring tribes. Journal of medical Internet research Vol. 14, 6 (2012).Google ScholarCross Ref
Index Terms
- Information Sources and Needs in the Obesity and Diabetes Twitter Discourse
Recommendations
Analyzing use of Twitter by diabetes online community
ASONAM '19: Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and MiningSocial Media platforms have become common venue for sharing experiences and knowledge about health-related topics. This research focuses on examining social media based communication patterns related to diabetes on the Twitter platform. Specifically, we ...
Information resonance on Twitter: watching Iran
SOMA '10: Proceedings of the First Workshop on Social Media AnalyticsTwitter has undoubtedly caught the attention of both the general public, and academia as a microblogging service worthy of study and attention. Twitter has several features that sets it apart from other social media/networking sites, including its 140 ...
The Dynamics of (Not) Unfollowing Misinformation Spreaders
WWW '24: Proceedings of the ACM on Web Conference 2024Many studies explore how people "come into" misinformation exposure. But much less is known about how people "come out of" misinformation exposure.Do people organically sever ties to misinformation spreaders? And what predicts doing so? Over six months, ...
Comments