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.

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中文翻译：

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社交媒体上神经性厌食症的特征：文本、视觉、关系、行为和人口统计分析


背景：饮食失调是一种以不健康饮食习惯为特征的心理疾病。神经性厌食症 (AN) 被定义为尽管体重严重不足，却仍相信体重超重。心理迹象涉及情绪和行为问题。有证据表明，体征和症状可以在社交媒体上表现出来，每天都会分享有害和有益的内容。目的：本研究旨在通过行为、人口统计、关系和多模态数据的提取和推断来描述 Twitter 上表现出厌食症状的西班牙语用户的特征。通过使用健康行为变化的跨理论模型，我们重点描述和比较处于克服 AN 模型不同阶段的用户，包括治疗和完全恢复期。方法：我们分析了经历神经性厌食症不同阶段的 Twitter 用户的写作、发帖模式、社交关系和分享的图像，并比较了经历每个疾病阶段的用户与对照组用户（即没有患神经性厌食症的用户）之间的差异。一个）。我们还分析了其关注者（即研究参与者关注的用户）感兴趣的主题。我们使用聚类方法将处于疾病早期阶段（预想）的用户与那些认识到自己的行为有问题（预想）的用户区分开来，并生成用于检测与 AN 相关的推文和图像的模型。我们考虑了两种类型的控制用户——集中控制用户，即使用与厌食症相关术语的用户，以及随机控制用户。结果：我们发现恢复过程每个阶段的用户与对照组之间存在显着差异 (P<.001)。 与随机对照用户 (STTR=0.04) 和集中对照用户 (STTR=0.03) 相比，AN 用户在夜间发推文更频繁，中位睡眠时间推文比率 (STTR) 为 0.05。图片与用户的特征相关。集中控制用户和随机控制用户的特征是在其个人资料图片中使用文本。我们还发现，专注控制用户和处于障碍第一阶段的用户之间存在强烈的两极分化。 AN 用户与其关注者之间的共同兴趣之间存在很强的相关性（ρ=0.96）。此外，与 AN 用户 (ρ=0.67) 相比，康复用户和治疗中用户的兴趣与关注对照组 (ρ=0.87) 的相关性更高，这表明用户在治疗期间的兴趣发生了变化。恢复过程。结论：我们将 AN 的症状映射到社交媒体环境中。这些结果支持了之前针对其他语言的研究结果，并涉及对用户在该疾病的每个阶段感兴趣的主题的深入分析。识别出的特征和模式为检测工具和推荐系统的开发提供了基础。


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