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Information Sources and Needs in the Obesity and Diabetes Twitter Discourse

Published:23 April 2018Publication History

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.

References

  1. 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 ScholarGoogle ScholarDigital LibraryDigital Library
  2. 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 ScholarGoogle Scholar
  3. 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 ScholarGoogle Scholar
  4. 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 ScholarGoogle Scholar
  5. 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 ScholarGoogle ScholarCross RefCross Ref
  6. 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 ScholarGoogle ScholarCross RefCross Ref
  7. 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 ScholarGoogle Scholar
  8. CDC. 2018. National Diabetes Statistics Report, 2018. National Center for Chronic Disease Prevention and Health Promotion (2018).Google ScholarGoogle Scholar
  9. 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 ScholarGoogle ScholarCross RefCross Ref
  10. 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 ScholarGoogle Scholar
  11. 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 ScholarGoogle ScholarCross RefCross Ref
  12. 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 ScholarGoogle Scholar
  13. 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 ScholarGoogle ScholarCross RefCross Ref
  14. 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 ScholarGoogle Scholar
  15. 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 ScholarGoogle ScholarCross RefCross Ref
  16. 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 ScholarGoogle ScholarCross RefCross Ref
  17. David M Garner. 1997. The 1997 body image survey results. Psychology today Vol. 30, 1 (1997), 30--44.Google ScholarGoogle Scholar
  18. 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 ScholarGoogle Scholar
  19. 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 ScholarGoogle ScholarCross RefCross Ref
  20. 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 ScholarGoogle Scholar
  21. 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 ScholarGoogle Scholar
  22. 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 ScholarGoogle Scholar
  23. 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 ScholarGoogle ScholarDigital LibraryDigital Library
  24. 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 ScholarGoogle Scholar
  25. 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 ScholarGoogle Scholar
  26. Taha A Kass-Hout and Hend Alhinnawi. 2013. Social media in public health. British Medical Bulletin Vol. 108, 1 (2013), 5--24.Google ScholarGoogle ScholarCross RefCross Ref
  27. Anna Kata. 2010. A postmodern Pandora's box: anti-vaccination misinformation on the Internet. Vaccine Vol. 28, 7 (2010), 1709--1716.Google ScholarGoogle ScholarCross RefCross Ref
  28. 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 ScholarGoogle Scholar
  29. 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 ScholarGoogle ScholarCross RefCross Ref
  30. 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 ScholarGoogle ScholarDigital LibraryDigital Library
  31. 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 ScholarGoogle ScholarCross RefCross Ref
  32. Yelena Mejova, Sofiane Abbar, and Hamed Haddadi. 2016. Fetishizing Food in Digital Age:# foodporn Around the World. ICWSM. 250--258.Google ScholarGoogle Scholar
  33. 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 ScholarGoogle ScholarDigital LibraryDigital Library
  34. 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 ScholarGoogle Scholar
  35. 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 ScholarGoogle ScholarCross RefCross Ref
  36. 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 ScholarGoogle Scholar
  37. James O. Prochaska and Carlo C. DiClemente. 2005. The Transtheoretical Approach. Handbook of psychotherapy integration (2005).Google ScholarGoogle Scholar
  38. 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 ScholarGoogle Scholar
  39. 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 ScholarGoogle ScholarCross RefCross Ref
  40. 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 ScholarGoogle Scholar
  41. Jane Sarasohn-Kahn. 2008. The wisdom of patients: Health care meets online social media. (2008).Google ScholarGoogle Scholar
  42. 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 ScholarGoogle Scholar
  43. 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 ScholarGoogle Scholar
  44. 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 ScholarGoogle Scholar
  45. 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 ScholarGoogle ScholarCross RefCross Ref
  46. 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 ScholarGoogle ScholarDigital LibraryDigital Library
  47. 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 ScholarGoogle Scholar
  48. 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 ScholarGoogle ScholarDigital LibraryDigital Library
  49. J. Kevin Thomson and Lauren Schaefer. 2018. Body Image, Obesity, and Eating Disorders. Eating Disorders and Obesity: A Comprehensive Handbook (2018), 140.Google ScholarGoogle Scholar
  50. 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 ScholarGoogle Scholar
  51. 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 ScholarGoogle Scholar
  52. 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 ScholarGoogle Scholar
  53. 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 ScholarGoogle ScholarCross RefCross Ref
  54. 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 ScholarGoogle Scholar
  55. 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 ScholarGoogle ScholarCross RefCross Ref

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          cover image ACM Conferences
          DH '18: Proceedings of the 2018 International Conference on Digital Health
          April 2018
          172 pages
          ISBN:9781450364935
          DOI:10.1145/3194658

          Copyright © 2018 ACM

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          Publication History

          • Published: 23 April 2018

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