Skip to main content

Obesity in social media: a mixed methods analysis


The escalating obesity rate in the USA has made obesity prevention a top public health priority. Recent interventions have tapped into the social media (SM) landscape. To leverage SM in obesity prevention, we must understand user-generated discourse surrounding the topic. This study was conducted to describe SM interactions about weight through a mixed methods analysis. Data were collected across 60 days through SM monitoring services, yielding 2.2 million posts. Data were cleaned and coded through Natural Language Processing (NLP) techniques, yielding popular themes and the most retweeted content. Qualitative analyses of selected posts add insight into the nature of the public dialogue and motivations for participation. Twitter represented the most common channel. Twitter and Facebook were dominated by derogatory and misogynist sentiment, pointing to weight stigmatization, whereas blogs and forums contained more nuanced comments. Other themes included humor, education, and positive sentiment countering weight-based stereotypes. This study documented weight-related attitudes and perceptions. This knowledge will inform public health/obesity prevention practice.

This is a preview of subscription content, access via your institution.


  1. 1.

    Ata RN, Thompson JK. Weight bias in the media: a review of recent research. Obes Facts. 2010; 3: 41-46. doi:10.1016/j.bodyim.2010.10.003.

    PubMed  Article  Google Scholar 

  2. 2.

    Chou WY, Hunt YM, Beckjord EB, Moser RP, Hesse BW. Social media use in the United States: implications for health communication. J Med Internet Res. 2009; 11: e48. doi:10.2196/jmir.1249.

    PubMed  Article  PubMed Central  Google Scholar 

  3. 3.

    Chou WS, Prestin A, Lyons C, Wen K. Web 2.0 for health promotion: reviewing the current evidence. Am J Public Health. 2013; 103(1): e9-e18. doi:10.2105/AJPH.2012.301071.

    PubMed  Article  Google Scholar 

  4. 4.

    Christopherson KM. The positive and negative implications of anonymity in Internet social interactions: “On the Internet, Nobody Knows You’re a Dog. Computers and Human Behavior. 2007; 23(6): 3038-3056. doi:10.1016/j.chb.2006.09.001.

    Article  Google Scholar 

  5. 5.

    Dickins M, Thomas SL, King B, Lewis S, Holland K. The role of the fatosphere in fat adults’ responses to obesity stigma: a model of empowerment without a focus on weight loss. Qual Health Res. 2011; 21(12): 1679-1691. doi:10.1177/1049732311417728.

    PubMed  Article  Google Scholar 

  6. 6.

    Domoff SE, Hinman NG, Koball AM, et al. The effects of reality television on weight bias: an examination of The Biggest Loser. Obesity. 2012; 20: 993-998. doi:10.1038/oby.2011.378.

    PubMed  Article  Google Scholar 

  7. 7.

    Fikkan JL, Rothblum ED. Is fat a feminist issue? Exploring the gendered nature of weight bias. Sex Roles. 2011; 66: 575-592. doi:10.1007/s11199-011-0022-5.

    Article  Google Scholar 

  8. 8.

    Fouts G, Burggraf K. Television situation comedies: female weight, male negative comments, and audience reactions. Sex Roles. 2000; 42: 925-932. doi:10.1023/a:1007054618340.

    Article  Google Scholar 

  9. 9.

    Freis SD, Gurung RAR. A Facebook analysis of helping behavior in online bullying. Psychology of Popular Media Culture. 2013; 2: 11-19. doi:10.1037/a0030239.

    Article  Google Scholar 

  10. 10.

    Greenberg BS, Eastin M, Hofschire L, Lachlan K, Brownell KD. Portrayals of overweight and obese individuals on commercial television. Am J Public Health. 2003; 93: 1342-1348.

    PubMed  Article  PubMed Central  Google Scholar 

  11. 11.

    Harrison K. Television viewing, fat stereotyping, body shape standards, and eating disorder symptomatology in grade school children. Commun Res. 2000; 27: 617-640. doi:10.1177/009365000027005003.

    Article  Google Scholar 

  12. 12.

    Hinduja S, Patchin JW. Bullying, cyberbullying, and suicide. Arch Suicide Res. 2010; 14: 206-221. doi:10.1080/13811118.2010.494133.

    PubMed  Article  Google Scholar 

  13. 13.

    Hussin M, Frazier S, Thompson JK. Fat stigmatization on YouTube: a content analysis. Body Image. 2011; 8: 90-92. doi:10.1016/j.bodyim.2010.10.003.

    PubMed  Article  Google Scholar 

  14. 14.

    Hwang KO, Etchegaray JM, Sciamanna CN, Bernstam EV, Thomas EJ. Structural social support predicts functional social support in an online weight loss programme. Health Expect. 2011. doi:10.1111/j.1369-7625.2011.00759.x.

    Google Scholar 

  15. 15.

    Hwang KO, Ning J, Trickey AW, Sciamanna CN. Website usage and weight loss in a free commercial online weight loss program: retrospective cohort study. J Med Internet Res. 2013; 15: e11. doi:10.2196/jmir.2195.

    PubMed  Article  PubMed Central  Google Scholar 

  16. 16.

    Hwang KO, Ottenbacher AJ, Green AP, et al. Social support in an Internet weight loss community. International Journal of Medical Information. 2010; 79: 5-13. doi:10.1016/j.ijmedinf.2009.10.003.

    Article  Google Scholar 

  17. 17.

    Hwang KO, Ottenbacher AJ, Lucke JF, et al. Measuring social support for weight loss in an internet weight loss community. J Health Commun. 2011; 16: 198-211. doi:10.1080/10810730.2010.535106.

    PubMed  Article  Google Scholar 

  18. 18.

    Kim S-H, Anne Willis L. Talking about obesity: news framing of who is responsible for causing and fixing the problem. J Health Commun. 2007; 12: 359-376. doi:10.1080/10810730701326051.

    PubMed  Article  Google Scholar 

  19. 19.

    Klein H, Shiffman KS. Thin is “in” and stout is “out”: what animated cartoons tell viewers about body weight. Eat Weight Disord. 2005; 10: 107-116. doi:10.1007/BF03327532.

    PubMed  Article  CAS  Google Scholar 

  20. 20.

    Lapidot-Lefler N, Barak A. Effects of anonymity, invisibility, and lack of eye-contact on toxic online disinhibition. Computers and Human Behavior. 2012; 28: 434-443. doi:10.1016/j.chb.2011.10.014.

    Article  Google Scholar 

  21. 21.

    Latner JD, Rosewall JK, Simmonds MB. Childhood obesity stigma: association with television, videogame, and magazine exposure. Body Image. 2007; 4: 147-155. doi:10.1016/j.bodyim.2007.03.002.

    PubMed  Article  Google Scholar 

  22. 22.

    Lewis S, Thomas SL, Blood RW, Castle D, Hyde J, Komesaroff PA. ‘I’m searching for solutions’: why are obese individuals turning to the Internet for help and support with ‘being fat’? Health Expect. 2011; 14: 339-350. doi:10.1111/j.1369-7625.2010.00644.x.

    PubMed  Article  Google Scholar 

  23. 23.

    Libbey HP, Story MT, Neumark-Sztainer DR, Boutelle KN. Teasing, disordered eating behaviors, and psychological morbidities among overweight adolescents. Obesity. 2008; 16(S2): S24-S29. doi:10.1038/oby.2008.455.

    PubMed  Article  Google Scholar 

  24. 24.

    Madden M (2012) Privacy management on social media sites. Washington, DC: Pew Research Center; 2012. Available at: Accessed July 1, 2013.

  25. 25.

    Major LH. Break it to me harshly: the effects of intersecting news frames in lung cancer and obesity coverage. J Health Commun. 2009; 14: 174-188. doi:10.1080/10810730802659939.

    PubMed  Article  Google Scholar 

  26. 26.

    National Center for Health Statistics (2011) Health, United States, 2011: with special feature on socioeconomic status and health. Hyattsville (MD): National Center for Health Statistics (US); 2012. Available at: Accessed July 5, 2013.

  27. 27.

    O’Sullivan PB, Flanagin AJ. Reconceptualizing “flaming” and other problematic messages. New Media & Society. 2003; 5: 69-94. doi:10.1177/1461444803005001908.

    Article  Google Scholar 

  28. 28.

    Pagoto SL, Schneider KL, Oleski J, Smith B, Bauman M (2013) The adoption and spread of a core-strengthening exercise through an online social network. Journal of Physical Activity and Health, (online ahead of print).

  29. 29.

    Poirier J, Cobb NK. Social influence as a driver of engagement in a web-based health intervention. J Med Internet Res. 2012; 14(1): e36. doi:10.2196/jmir.1957.

    PubMed  Article  PubMed Central  Google Scholar 

  30. 30.

    Puhl R, Brownell KD. Bias, discrimination, and obesity. Obes Res. 2001; 9: 788-805. doi:10.1038/oby.2001.108.

    PubMed  Article  CAS  Google Scholar 

  31. 31.

    Puhl RM, Brownell KD. Psychosocial origins of obesity stigma: toward changing a powerful and pervasive bias. Obes Rev. 2003; 4: 213-227. doi:10.1046/j.1467-789X.2003.00122.x.

    PubMed  Article  CAS  Google Scholar 

  32. 32.

    Puhl RM, Brownell KD. Confronting and coping with weight stigma: an investigation of overweight and obese adults. Obesity. 2006; 14(10): 1802-1815. doi:10.1038/oby.2006.208.

    PubMed  Article  Google Scholar 

  33. 33.

    Puhl RM, Heuer CA. The stigma of obesity: a review and update. Obesity. 2009; 17(5): 941-964. doi:10.1038/oby.2008.636.

    PubMed  Article  Google Scholar 

  34. 34.

    Puhl RM, Heuer CA. Obesity stigma: important considerations for public health. Am J Public Health. 2010; 100(6): 1019-1028. doi:10.2105/AJPH.2009.159491.

    PubMed  Article  PubMed Central  Google Scholar 

  35. 35.

    Puhl RM, Luedicke J, Peterson LJ. Public reactions to obesity-related health campaigns. Am J Prev Med. 2013; 45: 36-48. doi:10.1016/j.amepre.2013.02.010.

    PubMed  Article  Google Scholar 

  36. 36.

    Puhl RM, Peterson JL, DePierre JA, Luedicke J. Headless, hungry, and unhealthy: a video content analysis of obese persons portrayed in online news. J Health Commun. 2013; 18: 686-702. doi:10.1080/10810730.2012.743631.

    PubMed  Article  Google Scholar 

  37. 37.

    Rudman LA, Feinberg J, Fairchild K. Minority members’ implicit attitudes: automatic ingroup bias as a function of group status. Soc Cogn. 2002; 20: 294-320. doi:10.1521/soco.

    Article  Google Scholar 

  38. 38.

    Smith N, Wickes R, Underwood M. Managing a marginalised identity in pro-anorexia and fat acceptance cybercommunities. J Sociol. 2013. doi:10.1177/1440783313486220.

    Google Scholar 

  39. 39.

    Sonneville KR, Calzo JP, Horton NJ, Haines J, Austin SB, Field AE. Body satisfaction, weight gain and binge eating among overweight adolescent girls. Int J Obes (Lond). 2012; 36(7): 944-949. doi:10.1038/ijo.2012.68.

    Article  CAS  Google Scholar 

  40. 40.

    Sproull L, Kiesler S. Connections: New Ways of Working in the Networked Organization. Cambridge, MA: MIT Press; 1992.

    Google Scholar 

  41. 41.

    Storch E, Larson M, Ehrenreich-May J, Jones AE, Renno A, et al. Peer victimization in youth with autism spectrum disorders and co-occurring anxiety: relations with psychopathology and loneliness. J Dev Phys Disabil. 2012. doi:10.1007/s10882-012-9290-4.

    Google Scholar 

  42. 42.

    Suisman JL, Slane JD, Burt SA, Klump KL. Negative affect as a mediator of the relationship between weight-based teasing and binge eating in adolescent girls. Eat Behav. 2008; 9(4): 493-496. doi:10.1016/j.eatbeh.2008.04.001.

    PubMed  Article  PubMed Central  Google Scholar 

  43. 43.

    Suler J. The online disinhibition effect. Cyberpsychology and Behavior. 2004; 7: 321-326. doi:10.1089/1094931041291295.

    PubMed  Article  Google Scholar 

  44. 44.

    Thomas S, Hyde J, Komesaroff P. “Cheapening the struggle”: obese people’s attitudes toward The Biggest Loser. Obes Manag. 2007; 3: 210-215. doi:10.1089/obe.2007.0065.

    Article  Google Scholar 

  45. 45.

    Twitter (2012) Twitter turns six. Twitter Blog. Available at: Accessed July 5, 2012.

  46. 46.

    Vartanian LR. Disgust and perceived control in attitudes toward obese people. Int J Obes (Lond). 2010; 34: 1302-1307. doi:10.1038/ijo.2010.45.

    Article  CAS  Google Scholar 

  47. 47.

    Wang SS, Brownell KD, Wadden TA. The influence of the stigma of obesity on overweight individuals. International Journal of Obesity Related Metabolic Disorders. 2004; 28(10): 1333-1337.

    PubMed  Article  CAS  Google Scholar 

  48. 48.

    Ybarra ML, Mitchell KJ. Youth engaging in online harassment: associations with caregiver–child relationships, Internet use, and personal characteristics. J Adolesc. 2004; 27: 319-336. doi:10.1016/j.adolescence.2004.03.007.

    PubMed  Article  Google Scholar 

  49. 49.

    Yoo JH. No clear winner: effects of The Biggest Loser on the stigmatization of obese persons. Health Commun. 2013; 28: 294-303. doi:10.1080/10410236.2012.684143.

    PubMed  Article  Google Scholar 

  50. 50.

    Yoo JH, Kim J. Obesity in the new media: a content analysis of obesity videos on YouTube. Health Commun. 2012; 27: 86-97. doi:10.1080/10410236.2011.569003.

    PubMed  Article  Google Scholar 

  51. 51.

    Zimbardo PG. The human choice: individuation, reason, and order versus deindividuation, impulse, and chaos. Nebr Symp Motiv. 1969; 17: 237-307.

    Google Scholar 

Download references


Data collection for this project was enabled through the support of the National Institute on Minority Health and Health Disparities and the National Cancer Institute.

Author information



Corresponding author

Correspondence to Wen-ying Sylvia Chou PhD, MPH.

Additional information


Practice: Public health practitioners and health-care providers must be aware of the nature of authentic online conversations surrounding obesity, including negative sentiment that could drown out health messages as well as positive, health-promoting sentiment, and consider ways to leverage ongoing conversations to counter weight-based stigma.

Policy: Broader efforts can be implemented to curb online weight stigma, by partnering with existing anti-cyberbullying efforts and online “influencers” such as celebrity figures to affect the dialogue over time.

Research: This work offers insights into the lived experience of obesity. It will inform research investigating the efficacy and effectiveness of health promotion and weight control interventions using social media.

About this article

Cite this article

Chou, Wy.S., Prestin, A. & Kunath, S. Obesity in social media: a mixed methods analysis. Behav. Med. Pract. Policy Res. 4, 314–323 (2014).

Download citation


  • Obesity
  • Weight stigma
  • Cyber aggression
  • Social media
  • Health communication
  • Mixed methods
  • Online social support