Characterization of anorexia nervosa on social media: textual, visual, relational, behavioral, and demographical analysis

Ramírez Cifuentes, Diana; Freire, Ana; Baeza Yates, Ricardo; Sanz Lamora, Nadia; Álvarez, Aida; González Rodríguez, Alexandre; Lozano Rochel, Meritxell; Llobet Vives, Roger; Velazquez, Diego Alejandro; Gonfaus, Josep Maria; Gonzàlez, Jordi

doi:http://dx.doi.org/10.2196/25925

Characterization of anorexia nervosa on social media: textual, visual, relational, behavioral, and demographical analysis

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Ramírez-Cifuentes D, Freire A, Baeza-Yates R, Sanz Lamora N, Álvarez A, González-Rodríguez A, Lozano Rochel M, Llobet Vives R, Velazquez DA, Gonfaus JM, Gonzàlez J. Characterization of anorexia nervosa on social media: textual, visual, relational, behavioral, and demographical analysis. J Med Internet Res 2021;23(7):e25925. DOI: 10.2196/25925

Abstract

Background: Eating disorders are psychological conditions characterized by unhealthy eating habits. Anorexia nervosa (AN) is defined as the belief of being overweight despite being dangerously underweight. The psychological signs involve emotional and behavioral issues. There is evidence that signs and symptoms can manifest on social media, wherein both harmful and beneficial content is shared daily. Objective: This study aims to characterize Spanish-speaking users showing anorexia signs on Twitter through the extraction and inference of behavioral, demographical, relational, and multimodal data. By using the transtheoretical model of health behavior change, we focus on characterizing and comparing users at the different stages of the model for overcoming AN, including treatment and full recovery periods. Methods: We analyzed the writings, posting patterns, social relationships, and images shared by Twitter users who underwent different stages of anorexia nervosa and compared the differences among users going through each stage of the illness and users in the control group (ie, users without AN). We also analyzed the topics of interest of their followees (ie, users followed by study participants). We used a clustering approach to distinguish users at an early phase of the illness (precontemplation) from those that recognize that their behavior is problematic (contemplation) and generated models for the detection of tweets and images related to AN. We considered two types of control users—focused control users, which are those that use terms related to anorexia, and random control users. Results: We found significant differences between users at each stage of the recovery process (P<.001) and control groups. Users with AN tweeted more frequently at night, with a median sleep time tweets ratio (STTR) of 0.05, than random control users (STTR=0.04) and focused control users (STTR=0.03). Pictures were relevant for the characterization of users. Focused and random control users were characterized by the use of text in their profile pictures. We also found a strong polarization between focused control users and users in the first stages of the disorder. There was a strong correlation among the shared interests between users with AN and their followees (ρ=0.96). In addition, the interests of recovered users and users in treatment were more highly correlated to those corresponding to the focused control group (ρ=0.87 for both) than those of AN users (ρ=0.67), suggesting a shift in users’ interest during the recovery process. Conclusions: We mapped the signs of AN to social media context. These results support the findings of previous studies that focused on other languages and involved a deep analysis of the topics of interest of users at each phase of the disorder. The features and patterns identified provide a basis for the development of detection tools and recommender systems.