Characterization of Anorexia Nervosa on Social Media: Textual, Visual, Relational, Behavioral, and Demographical Analysis

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.

Gender Bias When Using Artificial Intelligence to Assess Anorexia Nervosa on Social Media: Data-Driven Study

“…This can provide a characterization of the symptoms of psychological disorders such as AN. In this regard, the study by Ramírez-Cifuentes et al [5] characterized different stages of AN on Spanish-speaking Twitter users by combining the analysis of text, images, and social interactions.…”

“…On a daily basis, many people are increasingly using social media platforms to share their feelings and moods. This creates a unique opportunity to proactively identify linguistic patterns that correlate with mental disorders [5,6]. Early risk prediction of depression and anorexia [7] and suicide risk assessment [8,9] are just some examples of different initiatives that have fostered research on the interaction between language and mental health disorders on web-based social media and the application of ML to address such challenges.…”

Self-representations of the experience of anorexia on YouTube: The joint influence of the explanatory model and the web platform

“…Some researchers differentiate between communities that post about anorexia—for example, pro-ana, anti-ana, and pro-recovery communities (Chancellor et al, 2016). 2 They note specificities in the language used by pro-ana and pro-recovery people, such as the use of personal pronouns, the emotional tone of posts, and the topics raised (Chancellor et al, 2016; Ramírez-Cifuentes et al, 2021). However, contemporary scholarship on these communities has shown that the borders between them blur over time and might be considered artificial; therefore, it is questionable whether such distinctions are reasonable (Cobb, 2017; Wang et al, 2019).…”

Associations between the Avatar Characteristics and Psychometric Test Results of VK Social Media Users

“…The relations with the personality traits were found not only for the OSM photo avatars [1,9] but for people's avatars in other virtual activities [10,11]. In the area of psychological research, it was shown that avatars of individuals who are prone to depression often depict a single person and are biased toward the gray spectrum [12]. Similar relationships between the graphic content of a user's online social network profile and his, her or their psychological peculiarities can be traced for other conditions as well [12][13][14].…”

“…As noted earlier, such quantified relationships between an avatar's graphical characteristics and personality traits can be used in automated decision support systems [15] in various fields, such as marketing and psychological and career counseling. For example, there exist automated systems for determining depression [12,16]. Moreover, these associations can be viewed as a part of the user profiling process that plays an important role in assessing an estimation of the users' protection from social engineering attacks [17][18][19].…”