4.6 Article

Social interactions in online eating disorder communities: A network perspective

Journal

PLOS ONE
Volume 13, Issue 7, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0200800

Keywords

-

Funding

  1. Economic and Social Research Council [ES/J500161/1]
  2. Institute for Life Sciences, Web Science Institute and Social Science, University of Southampton
  3. Alan Turing Institute
  4. ESRC Doctoral Training Centre [ES/J500161/1]
  5. Institute for Life Sciences, WSI-RCSF, University of Southampton
  6. Institute for Life Sciences, SocSCI-SIRF, University of Southampton
  7. Alan Turing Institute, UK

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Online health communities facilitate communication among people with health problems. Most prior studies focus on examining characteristics of these communities in sharing content, while limited work has explored social interactions between communities with different stances on a health problem. Here, we analyse a large communication network of individuals affected by eating disorders on Twitter and explore how communities of individuals with different stances on the disease interact online. Based on a large set of tweets posted by individuals who self-identify with eating disorders online, we establish the existence of two communities: a large community reinforcing disordered eating behaviours and a second, smaller community supporting efforts to recover from the disease. We find that individuals tend to mainly interact with others within the same community, with limited interactions across communities and inter-community interactions characterized by more negative emotions than intra-community interactions. Moreover, by studying the associations between individuals' behavioural characteristics and interpersonal connections in the communication network, we present the first large-scale investigation of social norms in online health communities, particularly on how a community approves of individuals' behaviours. Our findings shed new light on how people form online health communities and can have broad clinical implications on disease prevention and online intervention.

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