Male Self-Reported Eating Disorders on Chinese Social Media: A Computational Analysis of Xiaohongshu Posts and Comments

Male Self-Reported Eating Disorders on Chinese Social Media: A Computational Analysis of Xiaohongshu Posts and Comments | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Male Self-Reported Eating Disorders on Chinese Social Media: A Computational Analysis of Xiaohongshu Posts and Comments Shaojie Yang, Sanle Zhao, Wesley Barnhart, Peiyi Wang, Yunyi Cheng, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9156420/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background Males with eating disorders (EDs) remain overlooked, particularly due to gendered stereotypes that characterize EDs as primarily affecting females. Social media provides a naturalistic context in which content creators disclose illness experiences and receive public feedback. This study used computational text analysis to examine how male ED experiences are discussed on Xiaohongshu (Little Red Note), a major Chinese social media platform. Methods We collected 502 posts from eight male self-reported ED content creators and 20,844 associated public comments posted between October 2021 and June 2025. In posts and comments, sentiment analysis was used to quantify emotional polarity (positive, neutral, negative), and latent Dirichlet Allocation topic modeling was used to identify semantic patterns. Results The posts were predominantly positive (57.0%), reflecting recovery motivation, while 22.9% expressed negative affect, and 20.1% were neutral. Three associated thematic categories were revealed:(1) Emotional Struggles and Meaning-Making around EDs , (2) Male Binge–Purge Episodes and Self-Rescue Attempts , and (3) Journaling Treatment, Control, and Recovery Journeys . Comments also showed mixed sentiment, with a majority of positive responses (48.1%), followed by negative (34.5%) and neutral (17.3%). Three themes appeared from the comments: (1) Body Image- and Eating-related Communication , (2) Empathic Care and Psychological Support , and (3) Male Body Ideals and Appearance Judgments . Conclusion Male self-reported ED discourse on social media presents a mixed emotional landscape, yet positive sentiments reflect the majority of posts and comments. Computational analysis of naturalistic digital traces provides scalable insights into male self-reported EDs, underscoring the need for sex/gender-sensitive communication and platform-level strategies to support interventions. eating disorders men males social media sentiment analysis topic modeling Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Plain English Summary Eating disorders in men are often overlooked, and stigma can make it harder for men to seek help. In this study, we analyzed 502 Xiaohongshu posts from eight male content creators with self-reported eating disorders, along with 20,844 public comments. We examined the emotions and common themes in the posts and comments. Both showed mixed emotions, but positive expressions were more common overall. Posts often described emotional struggles, binge–purge cycles, and recovery efforts. Comments frequently included encouragement and empathy, but also body-focused judgments and advice related to male appearance ideals. This indicates that social media can serve as both a source of support and pressure for men with eating disorders. Platforms and interventions should consider gender-sensitive approaches that foster support while reducing harmful appearance-based feedback. 1. Introduction Eating disorders (EDs), such as anorexia nervosa, bulimia nervosa, and binge-eating disorder, are serious psychiatric conditions that are related to an array of negative health consequences, including elevated mortality, suicidality, mood disorders, medical complications, and impaired quality of life [ 1 , 2 ]. Although historically framed as conditions primarily affecting females, research consistently shows that males also experience clinically significant ED symptoms and associated impairment [ 3 , 4 ]. Compared with females, the etiology and symptomatology of male EDs often display unique features, such as simultaneous concerns with both leanness and muscularity [ 5 ]. Epidemiological research further indicates that ED behaviors are equally detrimental to males and may even produce greater psychosocial impairment in some domains [ 6 , 7 ]. For example, males tend to exhibit higher relative risks of hospitalization and mortality, particularly among individuals with anorexia nervosa[ 3 , 8 ], and males’ heightened drive for muscularity correlates with higher prevalence of substance use, increased depressive symptoms, and lower self-esteem[ 5 , 9 , 10 ]. Despite increasing awareness, EDs in males remain under-recognized and underdiagnosed/late diagnosed[ 4 , 11 ]. Gendered stereotypes frame EDs as “female illnesses,” contributing to shame, secrecy, denial, and reduced mental health help-seeking among men [ 7 , 12 , 13 , 14 , 15 ]. Stigma surrounding both mental health and deviations from dominant masculinity norms (e.g., assumptions that men should be strong, emotionally restrained, and unconcerned with body appearance) further suppresses disclosure and delays care utilization [ 16 , 17 ]. As a result, EDs in males are frequently overlooked in clinical settings[ 4 , 18 , 19 ], reinforcing a cycle in which invisibility is mistaken for the absence of need. In China, research focusing specifically on male EDs remains extremely limited. Beyond a few case reports and clinical descriptions[ 20 ], there have been few systematic epidemiological or qualitative investigations of Chinese males with EDs. Importantly, the limited population-based data available suggest that EDs are prevalent. For example, a questionnaire survey of 509 Chinese college freshmen in Chongqing and Shanghai found that approximately 1–2% of students met the Chinese diagnostic criteria and the DSM-III/DSM-III-R criteria for bulimia nervosa, with similar prevalence estimates across males and females[ 21 ]. Another school-based study of 1,320 females and 783 males aged 12–22 years reported that 2.24% of females and 0.90% of males endorsed full DSM-IV or EDNOS criteria for an ED[ 22 ]. Thus, the scarcity of male-focused research in China should not be interpreted as evidence of low prevalence estimates; rather, it likely reflects under-recognition. Consequently, many Chinese men with ED symptoms may remain undiagnosed or misdiagnosed. At the same time, evidence from Asia suggests that Asian males in these contexts may be more vulnerable to developing EDs than Western males due to their heightened “fear of fat”[ 23 ]. These gaps highlight the need for more research to illuminate how ED-related experiences are lived and articulated by males in China. Most research on male EDs has relied on surveys and qualitative interviews, which provide valuable insights, but may not capture spontaneous disclosure patterns or interactive feedback[ 24 – 27 ]. In contrast, social media offers a naturalistic space where individuals disclose symptoms, document recovery, and interact with others[ 28 – 30 ]. Prior research shows that online disclosure can foster connection and emotional relief, while large-scale digital trace data provide opportunities to study lived experiences beyond the constraints of clinical samples[ 31 – 33 ]. However, social media can also facilitate commentary that reflects skepticism, body-comparison pressures, or internalization of cultural appearance norms [ 34 , 35 ]. Thus, social media represents a complex communicative environment characterized by mixed emotional and evaluative responses. Notably, limited research has distinguished between self-disclosure by individuals with EDs and reactions from their audiences, despite these representing distinct yet interrelated social processes[ 36 , 37 ]. Computational text analysis approaches, such as sentiment analysis and Latent Dirichlet Allocation (LDA) topic modeling, can analyze large volumes of naturalistic online text to quantify emotional polarity and identify recurrent themes[ 38 – 40 ]. Such methods can reveal linguistic markers of distress, recovery processes, and potential early warning signals relevant to digital mental health interventions[ 41 , 42 ]. For example, in the ED domain, prior computational studies have successfully identified linguistic markers of anorexia narratives[ 43 ], examined public attitudes toward pro- and anti-anorexia content[ 44 ], and extracted ED-related themes from large-scale tweets[ 45 ]. Together, these findings demonstrate that sentiment analysis and LDA topic modeling can inform scalable detection, prevention, and intervention strategies within clinical and public health contexts[ 46 , 47 ]. Building on this framework, the present study applied sentiment analysis and topic modeling to posts and public comments regarding EDs in males on Xiaohongshu (Little Red Note), one of China’s largest social media platforms. Xiaohongshu was chosen as the study platform because, compared to other social media platforms (e.g., Weibo, Douyin), it focuses primarily on lifestyle and experience sharing, particularly on appearance, fitness, and beauty [ 48 ], and has been frequently used for investigating media discourse on body image and related topics[ 48 – 50 ]. Specifically, we sought to (Aim 1) identify the emotional patterns (positive, neutral, negative) that characterize male ED self-disclosure posts and public responses, and (Aim 2) determine the thematic structures emerging from posts and comments through topic modeling. By analyzing large-scale, naturalistic digital text, this study could illuminate how men in China articulate and negotiate self-reported ED experiences within online social spaces, offering insights for gender-sensitive communication and digital intervention design. 2. Method 2.1. Data Source and Sampling Strategy The project was approved by the Institutional Review Board of The Chinese University of Hong Kong, Shenzhen (“ Research on Social Media-based Machine Learning Identification and Prevention Strategies of Eating Disorders ”; No. EF20220809001). We gathered public post content and subsequent comment data from Xiaohongshu (Little Red Note). To identify male users who consistently documented self-reported ED–related experiences, we conducted keyword-based searches using ED-relevant terms in simplified Chinese, including “male [男],” “eating disorder [进食障碍],” “anorexia nervosa [厌食症/神经性厌食症],” “bulimia nervosa [贪食症/神经性贪食症],” and “binge-eating disorder [暴食症].” The final dataset consisted of 502 posts from eight male content creators with EDs and 20,844 associated public comments published between October 2021 and June 2025. A four-stage screening procedure was applied to obtain the data: (1) retrieval of all posts containing ED keywords; (2) application of visibility criteria (≥ 10 eating disorder–related posts and ≥ 100 followers) to ensure ongoing self-disclosure and audience engagement; Drawing on prior evidence that active content production and network connectivity better reflect social embeddedness in social media communities, minimum thresholds for ED-related posting activity and follower count were applied[ 51 , 52 ]. (3) manual review by two trained coders to confirm that content creators self-identified as males with self-reported EDs and that their posts reflected their own ED experiences rather than commercial, advertising, or unrelated content.(4) inclusion of text-based content only if it contained meaningful semantic information (which was manually reviewed by research assistants). Posts and comments were excluded if they contained fewer than five characters, consisted solely of emojis or symbols, were duplicated or bot-generated, included advertisements or personal privacy disclosures, or had been removed by platform moderation for harassment or illegal content. 2.2. Text Processing and Analytical Procedures All textual data were processed prior to analysis. Posts and comments were tokenized using the Jieba Chinese tokenizer, and standard Chinese stop-word lists (Jieba defaults plus an extended social media stop-word dictionary) were applied to remove non-informative words. Usernames, emojis, URLs, hashtags, and platform-generated markers were deleted, and semantically equivalent terms (e.g., variations of purging, vomiting, or binge eating) were merged to improve consistency across the corpus. Sentiment polarity (positive, neutral, negative) was computed using SnowNLP, a validated Chinese sentiment analysis model widely applied in social media research[ 53 ]. To enhance domain validity, we randomly selected 10% of posts and comments for dual human coding, and model performance was accepted when coder–model agreement exceeded 0.80; final polarity thresholds were set at ≥ 0.60 = positive, ≤ 0.40 = negative, and 0.40–0.60 = neutral. To extract semantic themes, we applied LDA topic modeling. A selective part-of-speech filtering process was employed. For the posts, only nouns (n), verbs (v), and adjectives (a) were retained to reduce redundancy. However, due to the unique characteristics of the comments, including their use of more tone particles and emotional expressions, no part-of-speech filtering was performed.The optimal number of topics was determined iteratively by jointly examining topic coherence (c_v, c_npmi), perplexity (held-out likelihood), u_mass, diversity (lexical non-redundancy across topic top words), balance (distributional evenness of topic prevalence), and the combined_score reported in the evaluation tables. No single index was treated as sufficient; instead, we adopted an evidence-convergence approach that prioritized consistency across indices and practical interpretability. 3. Results 3.1 Posts 3.1.1 Descriptive Analysis of Posts Descriptive analysis of 502 Xiaohongshu posts showed that their sentence length ranged from 1 to 97 characters, with an average of 16.26 characters and a standard deviation of 9.22; the 25th, 50th, and 75th percentiles are 12, 15, and 19 characters, respectively. This indicates that most Xiaohongshu posts were relatively short, with most falling between 12 and 19 characters. Short posts with no more than 10 characters accounted for 13.8% of the sample, while long posts with 30 characters or more accounted for 3.6%, suggesting that very short and very long posts are both minority cases, with the overall style on Xiaohongshu favoring moderately concise expressions. 3.1.2 Sentiment Analysis Sentiment analysis showed that male self-reported ED content creators expressed a mixed emotional profile, with predominantly positive sentiment, \(\:{\chi\:}^{2}\left(2\right)\:\) =126.82 ( p < .001). More than half of all posts (57.0%) were coded as positive (Fig. 1 ) . Word-frequency analysis ( Figure S1 ) showed that, beyond ED-related terms, the most frequent lexemes reflected recovery motivation and progress (e.g., “recover,” “rehabilitation”). Negative posts accounted for 22.9% (115 posts), and neutral posts were the least common (20.1%, 101 posts). For both negative and neutral categories, high-frequency words were primarily symptom-focused (e.g., “binge eating,” “purging,” “weight”) ( Figures S2–S3 ). 3.1.3 LDA Topic Analysis Through LDA modeling, three distinct thematic clusters were identified in content creators’ posts (Table 1 ). The number of three clusters was selected because it achieved a favorable balance between low perplexity and high topic coherence, yielding thematically distinct, human-interpretable topics suitable for psychologically meaningful inference and monitoring ( Table S1 ). Topic 1, Emotional Struggles and Meaning-Making around EDs , included emotional distress surrounding self-reported EDs and captured emotional distress related to self-reported EDs, including weight-loss efforts, depression and anxiety, and worries about body shape and health in everyday life. It depicted an ongoing search for meaning as individuals try to understand and live with self-reported EDs. Topic 2, Male Binge–Purge Episodes and Self-Rescue Attempts , centered on binge–purge experiences and subsequent “self-rescue” efforts, such as describing episodes of binge eating and purging and then setting rules or plans to regain control. Topic 3, Journaling Treatment, Control, and Recovery Journeys , reflected the use of posts as a recovery journal, including narratives about hospital admission and discharge, struggles with control over food, eating, and weight, and ongoing efforts to work toward recovery. Table 1 LDA modeling of posts ID Labels Terms 1 Emotional Struggles and Meaning-Making around EDs weight loss, depression, search, loss, need, eating, anorexia, everyone, at school, health, disorder, life, ED sufferers, anxiety, advice, body shape, develop, calculation, recovery, calories, as, see, diet, food, self-rescue, eat meals, guide, world, logic, underlying 2 Male Binge–Purge Episodes and Self-Rescue Attempts binge eating, boys, vomiting/purging, recording, milk tea, self-rescue, be able to, food, dinner, come out, height, give up, dinner, drinks, little boy, binge episode, stop binging, self-help, bravely face, effort, hold back, guide, avoid, appearance, cannot, anxiety, story, weight, share, anorexia nervosa 3 Journaling Treatment, Control, and Recovery Journeys eating, disorder, topics, rehabilitation, recovery, binge eating, appetite, vomiting/purging, anorexia nervosa, diet, weight loss, reflection, compulsion, food, weight, hospital admission, stability, time, calories, discharge from hospital, exercise, cannot, control, fear, meaning, unable to stop, walk out, method, change, everyone 3.1.4 Word Cloud and Frequency Analysis Word cloud and frequency analyses (Figs. 2 & 3 ) showed that content creators’ posts centered heavily on terms directly related to self-reported ED behaviors and recovery, such as “eating/eat,” “disorder,” “binge eating,” “purging,” “rehabilitation,” and “recovery.” Also, the frequent appearance of “male/boy [男/男生]” suggested that the content creator actively positions their experiences within the context of male identity. High-frequency use of verbs such as “quit,” “control,” “record,” and “recover” further indicated that the platform was used not only for emotional disclosure but also for self-monitoring and behavior tracking. 3.2 Public Comments 3.2.1. Sentence-Level Descriptive Analysis of Comments Descriptive analysis of 20,844 comments showed that the length of comment texts ranged from 1 to 300 characters, with a mean of 24.61 characters and a relatively large standard deviation of 30.19. The 25th, 50th, and 75th percentiles are 8, 15, and 29 characters, respectively, indicating that while many comments fall within a moderately short range, there were a few instances where the content is relatively longer, resulting in significant variability and a noticeable right tail. Short comments with no more than 10 characters accounted for 33.5% of the sample, whereas long comments with 30 characters or more accounted for 23.9%. 3.2.2 Sentiment Analysis of Public Comments Sentiment analysis of public comments (Fig. 4 ) similarly revealed a mixed emotional profile, χ²(2) = 1359.7, p < .001. Nearly half of the comments (48.1%) were positive. Word-frequency analysis showed that, in addition to eating/weight-related terms, frequent positive words included expressions of encouragement and empathy (e.g., “keep going,” “good”) ( Figure S4 ). Negative comments accounted for 34.5%, and neutral comments accounted for 17.3%. For both negative and neutral sentiment categories, the most frequent words were primarily related to eating and body image concerns ( Figures S5–S6 ). 3.2.3 LDA Topic Analysis of Comments LDA topic modeling identified three thematic clusters within public comments (Table 2 . Also, the number of three thematic clusters was selected because it maximized thematic diversity and maintained high topic exclusivity, with only negligible changes in perplexity relative to adjacent solutions ( Table S2 ). Topic 1, Body Image- and Eating-Related Communication , comprised interpersonal exchanges focused on appearance, eating, and food-related experiences. Comments frequently referred to the commenter’s own weight, food intake, and exercise routines, shared similar struggles, and posed questions to the blogger about their eating, strategies, or symptoms. Topic 2, Empathic Care and Psychological Support , centered on recovery-oriented messages, including expressions of empathy, encouragement, and psychological support (e.g., “keep going,” “cheer up,” or the Chinese term “孩子” [child], used in a caring way to convey warmth and concern), often urging content creators to persist with self-care. Topic 3, Male Body Ideals and Appearance Judgments , captured comments that evaluated the content creators’ body weight/shape and attractiveness in relation to male body ideals (e.g., height, muscularity, too thin, fitness, and strength), often accompanied by prescriptive appearance-related suggestions such as gaining muscle, changing weight, or increasing fitness. Table 2 LDA modeling of comments ID labels terms 1 Body Image- and Eating-Related Communication now, body weight, exactly, but, feeling, myself, binge eating, still, every day, lose weight, no, normal, body, food, can, time, how many, physical activity, not, can't, what, in this way, calories, eat, teacher, appetite, start, a day, how 2 Empathic Care and Psychological Support really, oneself, keep going, certainly, think, properly, already, health, child, wish, cheer up, thanks, recovery, such, us, these, slowly, life, more and more, condition, notice, why, unable, psychology, can, watch, possible, love, therefore, require 3 Male Body Ideals and Appearance Judgments body weight, this, should, may, height, if so, a bit, male, if, excuse me, suggestion, an, muscle, nice, aerobic exercise, female, fat loss, too thin, like, kilogram, suitable, check, hospital, fitness, muscle gain, laugh, lose weight again, strength, require, relatively 3.2.4 Word Cloud and Frequency Analysis of Comments Word cloud and frequency analyses of comments (Figs. 5 & 6 ) revealed highly interactive and evaluative language use. High-frequency words such as “eat,” “good,” “weight,” “not,” and terms associated with purging/vomiting indicate that commenters focused heavily on body image- and eating-related concerns, often directing feedback toward the content creators’ actions rather than simply observing them. Positive expressions (e.g., “keep up”) reflected interactive, supportive responses, whereas evaluative terms such as “weight,” “fat,” and “thin” suggested ongoing monitoring, judgment, or pressure related to body size and control. 4. Discussion Drawing on posts by male content creators with self-reported EDs and related public comments on the Chinese social media platform, Xiaohongshu, this study examined how this population discloses the ED experiences on Xiaohongshu and how the public responds, using sentiment analysis and topic modeling of 502 posts and 20,844 comments. Across both posts and comments, emotional expression was mixed but predominantly positive. The findings align with previous studies suggesting that social media can serve as an outlet for illness communication while simultaneously eliciting feedback[ 54 ]. The findings extend our understanding of male self-reported ED experiences in the Chinese context by situating them within a naturalistic, interactive digital environment. Although male self-reported ED content creators described profound emotional struggles associated with their self-reported EDs, positive sentiment was the dominant emotional tone. Posts frequently contained messages of hope, perseverance, and commitment to incremental recovery goals. Topic modeling further showed that content creators used the platform not only to describe their symptoms but also to engage in meaning-making around self-reported EDs, as well as to self-encourage and monitor their behaviors by documenting recovery efforts. The practices are plausibly driven by attempts to satisfy basic psychological needs for autonomy, competence, and relatedness[ 55 ]. Meanwhile, the theme we labeled Male Binge–Purge Episodes and Self-Rescue Attempts revealed detailed narratives of binge eating and purging, followed by self-help efforts. These narratives showed shifts between intense shame and self-blame and deliberate self-coaching and crisis-management strategies, indicating rapid emotional changes surrounding binge–purge episodes. Such fluctuations may contribute to the maintenance of the binge–purge cycle, consistent with prior findings that negative affect intensifies before binge eating and purging and decreases afterward, alongside corresponding changes in positive affect [ 56 ]. Public responses were mixed but predominantly positive, often offering emotional reassurance and encouragement for recovery. LDA analysis of comments revealed three coexisting themes: Empathic Care and Psychological Support ; Body Image and Eating-Related Communication ; and Male Body Ideals and Appearance Judgments . The first theme captured warm, affiliative exchanges (e.g., expressions of comfort and encouragement), whereas the latter two were dominated by appearance- and eating-focused talk. Commenters evaluated the content creators’ body size, weight, and attractiveness, shared their own eating and exercise experiences, and sometimes proposed specific strategies for changing weight, shape, or muscularity. The coexistence of encouragement and male-identity-based body image comments and judgments highlights that male self-reported ED disclosures are embedded within broader norms about what an idealized male body should look like (e.g., being tall, muscular, and strong rather than “too thin”). In this context, commenters simultaneously affirm and police men’s bodies through references to height, muscularity, and fitness. This blurred the boundary between support and surveillance and reinforced sex/gender-specific appearance pressures and body ideals. The pattern suggests that although social media can serve as a platform for support and facilitate connection and open communication, it also reproduces broader sociocultural pressures around body ideals and “unhealthy” eating/weight coping strategies[ 44 , 57 ]. Thus, social media becomes not only a site of support but also a site where norms about how the “ideal body” should look and behave are monitored and reinforced[ 58 ]. By applying computational analysis to naturalistic social media data, this study demonstrates that digital platforms can provide meaningful insight into how males experience and negotiate self-reported EDs and related public feedback. First, the predominance of positive sentiment in both posts and comments suggests that social media may serve as a source of informal, peer-based support, with public posting functioning as self-monitoring and positive reinforcement of recovery behaviors. Second, as warm and encouraging responses frequently coexist with body image- and eating-related communication and male-identity-based comments and judgments, the masculine norms can mask and normalize potentially harmful feedback. There is therefore a need for sex/gender-sensitive intervention strategies that explicitly acknowledge how masculine norms (e.g., strength, discipline, control, muscularity) shape both self-perception and the feedback received from others. For example, social media platforms can implement platform-supported warning that adds contextual health information to user-generated content, encouraging critical evaluation of potentially harmful social stigma. Third, because comment content frequently reflects weight- and shape-focused surveillance and communicates disordered eating and compensatory behaviors (e.g., binge eating, restriction, purging), platforms could use strategies to detect and flag or filter high-risk content[ 59 , 60 ] and prompt users toward evidence-based and safe resources. This study has limitations that offer directions for future research. First, the present study focused on a single social media platform and a limited sample of content creators. The relatively small dataset may limit the diversity of experiences, narrative styles, and emotional expressions captured. The identified topics and sentiment patterns may disproportionately reflect the perspectives of the subset of highly active users. The generalizability of the finding to other platforms or populations is therefore constrained. Models may also misclassify sentiment when expressions rely on sarcasm, metaphor, or culturally embedded meanings, leading to an inaccurate representation of some emotional signals. Additionally, the cross-sectional design limits inference about temporal change or causal effects of feedback. Future research should examine longitudinal posting dynamics (e.g., whether shifts in sentiment predict relapse or recovery) and integrate multimodal content (e.g., images and engagement metrics) to further explore the media disclosure of male EDs. Furthermore, among sexual minoritized men in China, eating and body image problems are closely associated with sexual self-labelling and gender expression[ 61 ]. This indicates the importance of incorporating comparison groups based on gender and sexual orientation when examining intersecting forms of stigma. Finally, although we focused on males with self-reported EDs, our search strategy targeted traditional self-reported EDs and did not explicitly include muscularity-oriented disordered eating (e.g., muscle dysmorphia, compulsive bulking/cutting, or anabolic-androgenic steroid use), which may be particularly salient and risky for males[ 9 , 62 ]. Future studies should explicitly capture these muscularity-related presentations and leverage social media data to develop platform-based detection, prevention, and intervention strategies tailored to muscularity-oriented disordered eating[ 63 ]. Overall, this study used sentiment analysis and topic modeling to characterize how males with self-reported EDs discuss their experiences and how viewers comment on those experiences. Emotional expression in both posts and comments was mixed yet predominantly positive, indicating that social media can function as a space for recovery-oriented self-expression and informal support. At the same time, public responses often paired encouragement with muscularity-oriented appearance commentary that promoted culturally salient male body ideals that centered on muscularity, height, and strength. The online community’s simultaneous promotion of warm support and norms about how the ideal body should look reinforced narrow male body ideals and normalized disordered eating and compensatory behaviors. These findings highlight the need for sex/gender-sensitive, platform-supported strategies that harness the supportive potential of social media while mitigating its risks. Abbreviations ED Eating disorders LDA Latent Dirichlet Allocation Declarations Conflict of Interest No potential conflict of interest was reported by the author(s). Funding Jinbo He was supported by the National Natural Science Foundation of China (Grant Number 72204208) and the 2022 Shenzhen College Stability Support Plan from the Shenzhen Science and Technology Innovation Commission (2022年度深圳市稳定支持计; Grant No. 2023SC0028). Author Contributions Shaojie Yang: Formal Analysis, Writing – original draft, and Writing–review & editing. Sanle Zhao: Writing – original draft, and Writing–review & editing. Wesley R. Barnhart: Writing – original draft, and Writing–review & editing. Peiyi Wang: Writing – original draft, and Writing–review & editing. Yunyi Cheng: Writing–review & editing. Bijie Tie: Writing–review & editing. Feng Ji: Supervision, and Writing–review & editing. Jinbo He: Conceptualization, Supervision, Funding acquisition, Writing – original draft, and Writing – review & editing. Ethical approval The project was approved by the Institutional Review Board (Applied Psychology) of The Chinese University of Hong Kong, Shenzhen (No. EF20220809001). Data Availability These data are available from the corresponding author upon request. Declaration of generative AI in scientific writing During the preparation of this work, the authors utilized GPT-5 to enhance the language of the manuscript. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the content of the published article. References Ágh T, Kovács G, Supina D, Pawaskar M, Herman BK, Vokó Z, Sheehan DV. A systematic review of the health-related quality of life and economic burdens of anorexia nervosa, bulimia nervosa, and binge eating disorder. Eating and Weight Disorders-Studies on Anorexia. Bulimia Obes. 2016;21(3):353–64. 10.1007/s40519-016-0264-x . Conti C, Lanzara R, Scipioni M, Iasenza M, Guagnano MT, Fulcheri M. The relationship between binge eating disorder and suicidality: a systematic review. Front Psychol. 2017;8:2125. 10.3389/fpsyg.2017.02125 . Brown TA, Keel PK. Eating Disorders in Boys and Men. Ann Rev Clin Psychol. 2023;19:177–205. 10.1146/annurev-clinpsy-080921-074125 . Strother E, Lemberg R, Stanford SC, Turberville D. Eating disorders in men: underdiagnosed, undertreated, and misunderstood. Eat Disord. 2012;20(5):346–55. 10.1080/10640266.2012.715512 . Calzo JP, Horton NJ, Sonneville KR, Swanson SA, Crosby RD, Micali N, Eddy KT, Field AE. Male Eating Disorder Symptom Patterns and Health Correlates From 13 to 26 Years of Age. J Am Acad Child Adolesc Psychiatry. 2016;55(8):693–e7002. 10.1016/j.jaac.2016.05.011 . Bentley C, Mond J, Rodgers B. Sex differences in psychosocial impairment associated with eating-disordered behavior: What if there aren't any? Eat Behav. 2014;15(4):609–14. 10.1016/j.eatbeh.2014.08.015 . Mitchison D, Mond J. Epidemiology of eating disorders, eating disordered behaviour, and body image disturbance in males: a narrative review. J Eat Disorders. 2015;3(1):20. 10.1186/s40337-015-0058-y . Iwajomo T, Bondy SJ, de Oliveira C, Colton P, Trottier K, Kurdyak P. Excess mortality associated with eating disorders: population-based cohort study. Br J Psychiatry. 2021;219(3):487–93. 10.1192/bjp.2020.197 . Lavender JM, Brown TA, Murray SB. Men, muscles, and eating disorders: an overview of traditional and muscularity-oriented disordered eating. Curr Psychiatry Rep. 2017;19(6):32. 10.1007/s11920-017-0787-5 . Nagata JM, Murray SB, Bibbins-Domingo K, Garber AK, Mitchison D, Griffiths S. Predictors of muscularity‐oriented disordered eating behaviors in US young adults: A prospective cohort study. Int J Eat Disord. 2019;52(12):1380–8. 10.1002/eat.23094 . Holder K. Eating Disorder Hospitalizations in the United States: Insights and Implications from the National Inpatient Sample [Doctoral dissertation, Johns Hopkins University]. Johns Hopkins University. 2025. Available from: https://jscholarship.library.jhu.edu/handle/1774.2/70761 Gorrell S, Murray SB. Eating disorders in males. Child and Adolescent Psychiatric Clinics of North America. 2019;28(4):641. 10.1016/j.chc.2019.05.012 Griffiths S, Mond JM, Murray SB, Touyz S. The prevalence and adverse associations of stigmatization in people with eating disorders. Int J Eat Disord. 2015;48(6):767–74. 10.1002/eat.22353 . Griffiths S, Mond JM, Murray SB, Touyz S. Young peoples' stigmatizing attitudes and beliefs about anorexia nervosa and muscle dysmorphia. Int J Eat Disord. 2014;47(2):189–95. 10.1002/eat.22220 . MacLean A, Sweeting H, Walker L, Patterson C, Räisänen U, Hunt K. It's not healthy and it's decidedly not masculine: a media analysis of UK newspaper representations of eating disorders in males. BMJ Open. 2015;5(5):e007468. 10.1136/bmjopen-2014-007468 . Lehe MS, Halbeisen G, Juergensen VC, Sabel L, Steins-Loeber S, Paslakis G. Boys don’t try? Gendered stigma specifically reduces help-seeking for disordered eating in men, but not women. J Eat Disorders. 2025;13(1):1–15. 10.1186/s40337-025-01407-7 . Richardson C, Paslakis G. Men’s experiences of eating disorder treatment: A qualitative systematic review of men-only studies. J Psychiatr Ment Health Nurs. 2021;28(2):237–50. 10.1111/jpm.12670 . Murray SB, Griffiths S, Nagata JM. Community-based eating disorder research in males: a call to action. J Adolesc Health. 2018;62(6):649–50. 10.1016/j.jadohealth.2018.03.008 . Murray SB, Griffiths S, Lavender JM. Introduction to a special issue on eating disorders and related symptomatology in male populations. Int J Eat Disord. 2019;52(12):1339–42. 10.1002/eat.23184 . Tong J, Miao SJ, Wang J, Zhang JJ, Wu HM, Li T, Hsu LG. Five cases of male eating disorders in Central China. Int J Eat Disord. 2005;37(1):72–5. 10.1002/eat.20061 . Chen ZF, et al. The prevalence of anorexia nervosa and bulimia nervosa among freshman medical college students in China. Int J Eat Disord. 1992;12(2):209–14. 10.1002/1098-108X(199209)12:2%3C209::AID-EAT2260120210%3E3.0.CO;2-%23 . Chen H, Jackson T. Prevalence and sociodemographic correlates of eating disorder endorsements among adolescents and young adults from China. Eur Eat Disorders Rev. 2008;16(5):375–85. 10.1002/erv.837 . Pike KM, Dunne PE. The rise of eating disorders in Asia: a review. J Eat Disorders. 2015;3(1):33. 10.1186/s40337-015-0070-2 . Robinson KJ, Mountford VA, Sperlinger DJ. Being men with eating disorders: Perspectives of male eating disorder service-users. J Health Psychol. 2013;18(2):176–86. 10.1177/1359105312440298 . Darcy AM, Lin IHJ. Are we asking the right questions? A review of assessment of males with eating disorders. Eat Disord. 2012;20(5):416–26. 10.1080/10640266.2012.715521 . Murray SB, Nagata JM, Griffiths S, Calzo JP, Brown TA, Mitchison D, Blashill JA, Mond JM. The enigma of male eating disorders: A critical review and synthesis. Clin Psychol Rev. 2017;57:1–11. 10.1016/j.cpr.2017.08.001 . Chapman J, Woodman T. Disordered eating in male athletes: a meta-analysis. J Sports Sci. 2016;34(2):101–9. 10.1080/02640414.2015.1040824 . Cavazos-Rehg PA, Krauss MJ, Costello SJ, Kaiser N, Cahn ES, Fitzsimmons-Craft EE, Wilfley DE. I just want to be skinny.: A content analysis of tweets expressing eating disorder symptoms. PLoS ONE. 2019;14(1):e0207506. 10.1371/journal.pone.0207506 . Moessner M, Feldhege J, Wolf M, Bauer S. Analyzing big data in social media: Text and network analyses of an eating disorder forum. Int J Eat Disord. 2018;51(7):656–67. 10.1002/eat.22878 . Wang T, Brede M, Ianni A, Mentzakis E. Social interactions in online eating disorder communities: A network perspective. PLoS ONE. 2018;13(7):e0200800. 10.1371/journal.pone.0200800 . Bickerstaff JM, Karim S, Whitman RK, Cypher A, Wiener S, Radovic A. You have people here to help you, people like me: A qualitative analysis of a blogging intervention for adolescents and young adults with depression or anxiety. J Technol Behav Sci. 2021;6(4):578–88. 10.1007/s41347-021-00210-w . Prescott J, Rathbone AL, Brown G. Online peer to peer support: Qualitative analysis of UK and US open mental health Facebook groups. Digit Health. 2020;6:2055207620979209. 10.1177/2055207620979209 . Strobel CB, Lennon J. Men in online eating disorder recovery spaces: Gendered barriers, content moderation, and narrative experimentation. Sociol Compass. 2023;17(11):e13156. 10.1111/soc4.13156 . Rounsefell K, Gibson S, McLean S, Blair M, Molenaar A, Brennan L, Truby H, McCaffrey TA. Social media, body image and food choices in healthy young adults: A mixed methods systematic review. Nutr Dietetics. 2020;77(1):19–40. 10.1111/1747-0080.12581 . Merino M, Tornero-Aguilera JF, Rubio-Zarapuz A, Villanueva-Tobaldo CV, Martín-Rodríguez A, Clemente-Suárez VJ. Body Perceptions and Psychological Well-Being: A Review of the Impact of Social Media and Physical Measurements on Self-Esteem and Mental Health with a Focus on Body Image Satisfaction and Its Relationship with Cultural and Gender Factors. Healthcare. 2024;12(14):1396. 10.3390/healthcare12141396 . Lonergan AR, Mitchison D, Bussey K, Fardouly J. Social media and eating and body image concerns among men and boys. Eating Disorders in Boys and Men. https://doi: Springer, Cham; 2021. pp. 307–16. 10.1007/978-3-030-67127-3_20 . Malova E, Dunleavy V. Men have eating disorders too: An analysis of online narratives posted by men with eating disorders on YouTube. Eat Disord. 2022;30(4):437–52. 10.1080/10640266.2021.1930338 . Rana TA, Cheah YN, Letchmunan S. Topic modeling in sentiment analysis: A systematic review. J ICT Res Appl. 2016;10(1). 10.5614/itbj.ict.res.appl.2016.10.1.6 . Jeong B, Yoon J, Lee JM. Social media mining for product planning: A product opportunity mining approach based on topic modeling and sentiment analysis. Int J Inf Manag. 2019;48:280–90. 10.1016/j.ijinfomgt.2017.09.009 . Melton CA, Olusanya OA, Ammar N, Shaban-Nejad A. Public sentiment analysis and topic modeling regarding COVID-19 vaccines on the Reddit social media platform: A call to action for strengthening vaccine confidence. J Infect Public Health. 2021;14(10):1505–12. 10.1016/j.jiph.2021.08.010 . Zhang T, Schoene AM, Ji S, Ananiadou S. Natural language processing applied to mental illness detection: a narrative review. NPJ Digit Med. 2022;5(1):46. 10.1038/s41746-022-00589-7 . Kim Y, Römer-Barron U. Detection and Analysis of Depression-Related Language in an Online Community: Machine Learning, Topic Modeling, and Corpus-Linguistic Approaches. Corpus-based Studies across Humanities. 2025. 10.1515/csh-2025-0005 Spinczyk D, Nabrdalik K, Rojewska K. Computer aided sentiment analysis of anorexia nervosa patients’ vocabulary. Biomed Eng Online. 2018;17(1):19. 10.1186/s12938-018-0451-2 . Oksanen A, Garcia D, Sirola A, Näsi M, Kaakinen M, Keipi T, Räsänen P. Pro-anorexia and anti-pro-anorexia videos on YouTube: Sentiment analysis of user responses. J Med Internet Res. 2015;17(11):e256. 10.2196/jmir.5007 . Zhou S, Zhao Y, Bian J, Haynos AF, Zhang R. Exploring eating disorder topics on Twitter: machine learning approach. JMIR Med Inf. 2020;8(10):e18273. 10.2196/18273 . Zunic A, Corcoran P, Spasic I. Sentiment analysis in health and well-being: systematic review. JMIR Med Inf. 2020;8(1):e16023. 10.2196/16023 . Liu Y, Shan Y, Sun S, Ji M, Zhou S, You Y, Liu H, Shen Y. Topic modeling and content analysis of people’s anxiety-related concerns raised on a computer-mediated health platform. Sci Rep. 2024;14(1):27520. 10.1038/s41598-024-79164-x . Lang M, Chen P, Li X, Ye Y. Refusing appearance anxiety: A content analysis of body positive posts on Chinese social media. Body Image. 2023;45:414–9. 10.1016/j.bodyim.2023.04.002 . Zhang C. Body Image and Social Media in China: Examining Body Image Discourses among Young Chinese Women on the Xiaohongshu Platform. J Int Crisis Risk Communication Res. 2024;7:1193–200. 10.63278/jicrcr.vi.2198 . Zhang J. The Impact of Pamela’s Fitness Content on Xiaohongshu on Women’s Body Anxiety: An Analysis of Visual Narrative and Emotion Mobilization. Literature Lang Cult Stud. 2025. 10.63313/LLCS.2006 . Arseniev-Koehler A, Lee H, McCormick T, Moreno MA, #Proana. Pro–eating disorder socialization on Twitter. J Adolesc Health. 2016;58(6):659–64. 10.1016/j.jadohealth.2016.02.012 . Sukunesan S, Huynh M, Sharp G. Examining the Pro-Eating Disorders Community on Twitter Via the Hashtag #proana: Statistical Modeling Approach. JMIR Mental Health. 2021;8(7):e24340. 10.2196/24340 . isnowfy. snownlp: Python library for processing Chinese text [Computer software]. GitHub. n.d. Available from: https://github.com/isnowfy/snownlp Au ES, Cosh SM. Social media and eating disorder recovery: An exploration of Instagram recovery community users and their reasons for engagement. Eat Behav. 2022;46:101651. 10.1016/j.eatbeh.2022.101651 . Li J, Tang L. I Want to Hold an Umbrella Over You Because I Have Been in the Rain: Exploring Patient Influencers’ Motivations to Share Eating Disorders Experiences from a Self-Determination Theory Perspective. Health Commun. 2025;40(11):2228–39. 10.1080/10410236.2024.2447103 . Harris EA, Moeck EK, Griffiths S. Affective Trajectories of Binge Eating, Purging, and Exercise Among Sexual Minority Men. Int J Eat Disord. 2025;58(5):939–51. 10.1002/eat.24406 . Logrieco G, Marchili MR, Roversi M, Villani A. The Paradox of TikTok Anti-Pro-Anorexia Videos: How Social Media Can Promote Non-Suicidal Self-Injury and Anorexia. Int J Environ Res Public Health. 2020;18(3):1041. 10.3390/ijerph18031041 . Strobel CB. The shadow that hovered over: Gender salience in eating disorder recovery. Gend Issues. 2022;39(3):368–86. 10.1007/s12147-022-09294-x . DiSalvo LM, Saenz GV, Wong WE, Li D. Social Media Safety Practices and flagging sensitive posts. In: 2022 IEEE 22nd International Conference on Software Quality, Reliability, and, Companion S. (QRS-C); 2022. IEEE; 2022. pp. 8–15. 10.1109/QRS-C57518.2022.00012 Podorozhniak A, Oliinyk V, Liubchenko N. Strategies for Filtering Unwanted Comments in Social Media. In: 2024 IEEE 5th KhPI Week on Advanced Technology (KhPIWeek); 2024. IEEE; 2024. pp. 1–4. 10.1109/KhPIWeek61434.2024.10877962 Barnhart WR, Han J, Zhang Y, Luo W, Li Y, He J. Differences in Thinness-and Muscularity-Oriented Eating and Body Image Disturbances and Psychosocial Well-Being in Chinese Sexual Minority Men Reporting Top, Bottom, and Versatile Sexual Self-Labels. Arch Sex Behav. 2024;53(10):3973–91. 10.1007/s10508-024-02962-x . Murray SB, Griffiths S, Mond JM. Evolving eating disorder psychopathology: Conceptualising muscularity-oriented disordered eating. Br J Psychiatry. 2016;208(5):414–5. 10.1192/bjp.bp.115.168427 . He J, Ji F. Artificial intelligence and social media for the detection of eating disorders. Int J Eat Disord. 2025;58(7):1187–90. 10.1002/eat.24438 . Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterials.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 01 May, 2026 Reviewers invited by journal 24 Mar, 2026 Editor assigned by journal 24 Mar, 2026 Submission checks completed at journal 24 Mar, 2026 First submitted to journal 18 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9156420","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":611625413,"identity":"f50e2551-c7c5-4f8d-9670-36d8b877b0cb","order_by":0,"name":"Shaojie Yang","email":"","orcid":"","institution":"Xi’an Jiaotong-Liverpool University","correspondingAuthor":false,"prefix":"","firstName":"Shaojie","middleName":"","lastName":"Yang","suffix":""},{"id":611625417,"identity":"5ae638ca-da31-40ca-b511-ed3044b52025","order_by":1,"name":"Sanle Zhao","email":"","orcid":"","institution":"Chinese University of Hong Kong, Shenzhen","correspondingAuthor":false,"prefix":"","firstName":"Sanle","middleName":"","lastName":"Zhao","suffix":""},{"id":611625420,"identity":"29937535-9b1d-4b90-b441-0492a4eb66af","order_by":2,"name":"Wesley Barnhart","email":"","orcid":"","institution":"Suffolk University","correspondingAuthor":false,"prefix":"","firstName":"Wesley","middleName":"","lastName":"Barnhart","suffix":""},{"id":611625422,"identity":"a090dfde-9116-4f6f-8b11-e03f8e1c62de","order_by":3,"name":"Peiyi Wang","email":"","orcid":"","institution":"The University of Texas Rio Grande Valley","correspondingAuthor":false,"prefix":"","firstName":"Peiyi","middleName":"","lastName":"Wang","suffix":""},{"id":611625423,"identity":"798c1d39-e961-42a1-a996-5e7618f4c7fd","order_by":4,"name":"Yunyi Cheng","email":"","orcid":"","institution":"Xi’an Jiaotong-Liverpool University","correspondingAuthor":false,"prefix":"","firstName":"Yunyi","middleName":"","lastName":"Cheng","suffix":""},{"id":611625425,"identity":"bfb537ff-2f59-4c1f-847e-0164c350c016","order_by":5,"name":"Bijie Tie","email":"","orcid":"","institution":"Southwest University","correspondingAuthor":false,"prefix":"","firstName":"Bijie","middleName":"","lastName":"Tie","suffix":""},{"id":611625426,"identity":"248fe159-52a2-42de-a04e-9a575631f477","order_by":6,"name":"Feng Ji","email":"","orcid":"","institution":"University of Toronto","correspondingAuthor":false,"prefix":"","firstName":"Feng","middleName":"","lastName":"Ji","suffix":""},{"id":611625428,"identity":"90baf5e2-421d-480e-8ece-ff6602857341","order_by":7,"name":"Jinbo He","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAu0lEQVRIiWNgGAWjYFAC5obPDAw2QAZj4wEitTA2zmZgSAMxGkjSchjMJE4L/+zGxuaCivN2a9sPA22psYkmqEXizsHG5hlnbidvO5MI1HIsLbeBoJ4bie2PedtuJ5sdAGphbDhMWIv8jcTGZt5/55LNzj8kUosBWEvDATuzG8TaYgjSwnMsOcHsBtCWBGL8Incj+WAzT42dvdn59IcPPtTYEOF9KEgEq0wgVjkI2JOieBSMglEwCkYYAADapUvwFawN/wAAAABJRU5ErkJggg==","orcid":"","institution":"Xi’an Jiaotong-Liverpool University","correspondingAuthor":true,"prefix":"","firstName":"Jinbo","middleName":"","lastName":"He","suffix":""}],"badges":[],"createdAt":"2026-03-18 08:09:59","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9156420/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9156420/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105497891,"identity":"966eae3f-2f58-47e4-a6ba-e04fa78cc5b5","added_by":"auto","created_at":"2026-03-26 16:52:36","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":496219,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSentiment analysis of the posts\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-9156420/v1/c69326e0381ffcfd17058c60.png"},{"id":105566611,"identity":"c7f1e453-34b7-4ec0-9dcb-045cfe9f89de","added_by":"auto","created_at":"2026-03-27 12:56:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1265199,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWord cloud analysis of posts\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-9156420/v1/c307939a3b1fe0d893d88781.png"},{"id":105497897,"identity":"1c71e062-0bf6-4974-bda1-06ba59fa7858","added_by":"auto","created_at":"2026-03-26 16:52:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":320266,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWord frequency analysis of the posts\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-9156420/v1/75d06d58056740b4a8de39e4.png"},{"id":105497893,"identity":"bbee5954-f4cb-413f-a7bb-ccd00dd91502","added_by":"auto","created_at":"2026-03-26 16:52:36","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":511850,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSentiment analysis of the comments\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-9156420/v1/7497dc5bf43de916a0051eb3.png"},{"id":105727951,"identity":"5a9a70a2-83d5-4ccb-94b7-fa10b13913db","added_by":"auto","created_at":"2026-03-30 11:06:13","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1322781,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWord cloud analysis of comments\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-9156420/v1/3553508eaed36add0d102c32.png"},{"id":105497895,"identity":"aad8f739-cb49-462b-a937-2fa6f0bd0811","added_by":"auto","created_at":"2026-03-26 16:52:36","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":95382,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWord frequency analysis of posts\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-9156420/v1/6bec38b2fe55a1ce3d03df83.png"},{"id":105752117,"identity":"f53042b1-014c-4408-a0c4-153aebfde1ef","added_by":"auto","created_at":"2026-03-30 15:55:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4863621,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9156420/v1/eb4845b9-a19c-4a89-ad3e-035dd12fdd5f.pdf"},{"id":105497892,"identity":"a8f4878a-7a0a-47a5-a1d9-d2917cc150ff","added_by":"auto","created_at":"2026-03-26 16:52:36","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":593197,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-9156420/v1/7e28a1e79305f50dc474102a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Male Self-Reported Eating Disorders on Chinese Social Media: A Computational Analysis of Xiaohongshu Posts and Comments","fulltext":[{"header":"Plain English Summary","content":"\u003cp\u003eEating disorders in men are often overlooked, and stigma can make it harder for men to seek help. In this study, we analyzed 502 Xiaohongshu posts from eight male content creators with self-reported eating disorders, along with 20,844 public comments. We examined the emotions and common themes in the posts and comments. Both showed mixed emotions, but positive expressions were more common overall. Posts often described emotional struggles, binge\u0026ndash;purge cycles, and recovery efforts. Comments frequently included encouragement and empathy, but also body-focused judgments and advice related to male appearance ideals. This indicates that social media can serve as both a source of support and pressure for men with eating disorders. Platforms and interventions should consider gender-sensitive approaches that foster support while reducing harmful appearance-based feedback.\u0026nbsp;\u003c/p\u003e\n"},{"header":"1. Introduction","content":"\u003cp\u003eEating disorders (EDs), such as anorexia nervosa, bulimia nervosa, and binge-eating disorder, are serious psychiatric conditions that are related to an array of negative health consequences, including elevated mortality, suicidality, mood disorders, medical complications, and impaired quality of life [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Although historically framed as conditions primarily affecting females, research consistently shows that males also experience clinically significant ED symptoms and associated impairment [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Compared with females, the etiology and symptomatology of male EDs often display unique features, such as simultaneous concerns with both leanness and muscularity [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Epidemiological research further indicates that ED behaviors are equally detrimental to males and may even produce greater psychosocial impairment in some domains [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. For example, males tend to exhibit higher relative risks of hospitalization and mortality, particularly among individuals with anorexia nervosa[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], and males\u0026rsquo; heightened drive for muscularity correlates with higher prevalence of substance use, increased depressive symptoms, and lower self-esteem[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite increasing awareness, EDs in males remain under-recognized and underdiagnosed/late diagnosed[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Gendered stereotypes frame EDs as \u0026ldquo;female illnesses,\u0026rdquo; contributing to shame, secrecy, denial, and reduced mental health help-seeking among men [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Stigma surrounding both mental health and deviations from dominant masculinity norms (e.g., assumptions that men should be strong, emotionally restrained, and unconcerned with body appearance) further suppresses disclosure and delays care utilization [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. As a result, EDs in males are frequently overlooked in clinical settings[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], reinforcing a cycle in which invisibility is mistaken for the absence of need.\u003c/p\u003e \u003cp\u003eIn China, research focusing specifically on male EDs remains extremely limited. Beyond a few case reports and clinical descriptions[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], there have been few systematic epidemiological or qualitative investigations of Chinese males with EDs. Importantly, the limited population-based data available suggest that EDs are prevalent. For example, a questionnaire survey of 509 Chinese college freshmen in Chongqing and Shanghai found that approximately 1\u0026ndash;2% of students met the Chinese diagnostic criteria and the DSM-III/DSM-III-R criteria for bulimia nervosa, with similar prevalence estimates across males and females[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Another school-based study of 1,320 females and 783 males aged 12\u0026ndash;22 years reported that 2.24% of females and 0.90% of males endorsed full DSM-IV or EDNOS criteria for an ED[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Thus, the scarcity of male-focused research in China should not be interpreted as evidence of low prevalence estimates; rather, it likely reflects under-recognition. Consequently, many Chinese men with ED symptoms may remain undiagnosed or misdiagnosed. At the same time, evidence from Asia suggests that Asian males in these contexts may be more vulnerable to developing EDs than Western males due to their heightened \u0026ldquo;fear of fat\u0026rdquo;[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. These gaps highlight the need for more research to illuminate how ED-related experiences are lived and articulated by males in China.\u003c/p\u003e \u003cp\u003eMost research on male EDs has relied on surveys and qualitative interviews, which provide valuable insights, but may not capture spontaneous disclosure patterns or interactive feedback[\u003cspan additionalcitationids=\"CR25 CR26\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In contrast, social media offers a naturalistic space where individuals disclose symptoms, document recovery, and interact with others[\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Prior research shows that online disclosure can foster connection and emotional relief, while large-scale digital trace data provide opportunities to study lived experiences beyond the constraints of clinical samples[\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. However, social media can also facilitate commentary that reflects skepticism, body-comparison pressures, or internalization of cultural appearance norms [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Thus, social media represents a complex communicative environment characterized by mixed emotional and evaluative responses.\u003c/p\u003e \u003cp\u003eNotably, limited research has distinguished between self-disclosure by individuals with EDs and reactions from their audiences, despite these representing distinct yet interrelated social processes[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Computational text analysis approaches, such as sentiment analysis and Latent Dirichlet Allocation (LDA) topic modeling, can analyze large volumes of naturalistic online text to quantify emotional polarity and identify recurrent themes[\u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Such methods can reveal linguistic markers of distress, recovery processes, and potential early warning signals relevant to digital mental health interventions[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. For example, in the ED domain, prior computational studies have successfully identified linguistic markers of anorexia narratives[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], examined public attitudes toward pro- and anti-anorexia content[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], and extracted ED-related themes from large-scale tweets[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Together, these findings demonstrate that sentiment analysis and LDA topic modeling can inform scalable detection, prevention, and intervention strategies within clinical and public health contexts[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBuilding on this framework, the present study applied sentiment analysis and topic modeling to posts and public comments regarding EDs in males on Xiaohongshu (Little Red Note), one of China\u0026rsquo;s largest social media platforms. Xiaohongshu was chosen as the study platform because, compared to other social media platforms (e.g., Weibo, Douyin), it focuses primarily on lifestyle and experience sharing, particularly on appearance, fitness, and beauty [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], and has been frequently used for investigating media discourse on body image and related topics[\u003cspan additionalcitationids=\"CR49\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Specifically, we sought to (Aim 1) identify the emotional patterns (positive, neutral, negative) that characterize male ED self-disclosure posts and public responses, and (Aim 2) determine the thematic structures emerging from posts and comments through topic modeling. By analyzing large-scale, naturalistic digital text, this study could illuminate how men in China articulate and negotiate self-reported ED experiences within online social spaces, offering insights for gender-sensitive communication and digital intervention design.\u003c/p\u003e"},{"header":"2. Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e2.1. Data Source and Sampling Strategy\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eThe project was approved by the Institutional Review Board of The Chinese University of Hong Kong, Shenzhen (\u0026ldquo;\u003cem\u003eResearch on Social Media-based Machine Learning Identification and Prevention Strategies of Eating Disorders\u003c/em\u003e\u0026rdquo;; No. EF20220809001). We gathered public post content and subsequent comment data from Xiaohongshu (Little Red Note). To identify male users who consistently documented self-reported ED\u0026ndash;related experiences, we conducted keyword-based searches using ED-relevant terms in simplified Chinese, including \u0026ldquo;male [男],\u0026rdquo; \u0026ldquo;eating disorder [进食障碍],\u0026rdquo; \u0026ldquo;anorexia nervosa [厌食症/神经性厌食症],\u0026rdquo; \u0026ldquo;bulimia nervosa [贪食症/神经性贪食症],\u0026rdquo; and \u0026ldquo;binge-eating disorder [暴食症].\u0026rdquo;\u003c/p\u003e \u003cp\u003eThe final dataset consisted of 502 posts from eight male content creators with EDs and 20,844 associated public comments published between October 2021 and June 2025. A four-stage screening procedure was applied to obtain the data: (1) retrieval of all posts containing ED keywords; (2) application of visibility criteria (\u0026ge;\u0026thinsp;10 eating disorder\u0026ndash;related posts and \u0026ge;\u0026thinsp;100 followers) to ensure ongoing self-disclosure and audience engagement; Drawing on prior evidence that active content production and network connectivity better reflect social embeddedness in social media communities, minimum thresholds for ED-related posting activity and follower count were applied[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. (3) manual review by two trained coders to confirm that content creators self-identified as males with self-reported EDs and that their posts reflected their own ED experiences rather than commercial, advertising, or unrelated content.(4) inclusion of text-based content only if it contained meaningful semantic information (which was manually reviewed by research assistants). Posts and comments were excluded if they contained fewer than five characters, consisted solely of emojis or symbols, were duplicated or bot-generated, included advertisements or personal privacy disclosures, or had been removed by platform moderation for harassment or illegal content.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Text Processing and Analytical Procedures\u003c/h2\u003e \u003cp\u003eAll textual data were processed prior to analysis. Posts and comments were tokenized using the Jieba Chinese tokenizer, and standard Chinese stop-word lists (Jieba defaults plus an extended social media stop-word dictionary) were applied to remove non-informative words. Usernames, emojis, URLs, hashtags, and platform-generated markers were deleted, and semantically equivalent terms (e.g., variations of purging, vomiting, or binge eating) were merged to improve consistency across the corpus. Sentiment polarity (positive, neutral, negative) was computed using SnowNLP, a validated Chinese sentiment analysis model widely applied in social media research[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. To enhance domain validity, we randomly selected 10% of posts and comments for dual human coding, and model performance was accepted when coder\u0026ndash;model agreement exceeded 0.80; final polarity thresholds were set at \u0026ge;\u0026thinsp;0.60\u0026thinsp;=\u0026thinsp;positive, \u0026le; 0.40\u0026thinsp;=\u0026thinsp;negative, and 0.40\u0026ndash;0.60\u0026thinsp;=\u0026thinsp;neutral. To extract semantic themes, we applied LDA topic modeling. A selective part-of-speech filtering process was employed. For the posts, only nouns (n), verbs (v), and adjectives (a) were retained to reduce redundancy. However, due to the unique characteristics of the comments, including their use of more tone particles and emotional expressions, no part-of-speech filtering was performed.The optimal number of topics was determined iteratively by jointly examining topic coherence (c_v, c_npmi), perplexity (held-out likelihood), u_mass, diversity (lexical non-redundancy across topic top words), balance (distributional evenness of topic prevalence), and the combined_score reported in the evaluation tables. No single index was treated as sufficient; instead, we adopted an evidence-convergence approach that prioritized consistency across indices and practical interpretability.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Posts\u003c/h2\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e3.1.1 Descriptive Analysis of Posts\u003c/h2\u003e \u003cp\u003eDescriptive analysis of 502 Xiaohongshu posts showed that their sentence length ranged from 1 to 97 characters, with an average of 16.26 characters and a standard deviation of 9.22; the 25th, 50th, and 75th percentiles are 12, 15, and 19 characters, respectively. This indicates that most Xiaohongshu posts were relatively short, with most falling between 12 and 19 characters. Short posts with no more than 10 characters accounted for 13.8% of the sample, while long posts with 30 characters or more accounted for 3.6%, suggesting that very short and very long posts are both minority cases, with the overall style on Xiaohongshu favoring moderately concise expressions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e3.1.2 Sentiment Analysis\u003c/h2\u003e \u003cp\u003eSentiment analysis showed that male self-reported ED content creators expressed a mixed emotional profile, with predominantly positive sentiment, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\chi\\:}^{2}\\left(2\\right)\\:\\)\u003c/span\u003e\u003c/span\u003e=126.82 (\u003cem\u003ep\u003c/em\u003e\u0026lt; .001). More than half of all posts (57.0%) were coded as positive (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Word-frequency analysis (\u003cb\u003eFigure S1\u003c/b\u003e) showed that, beyond ED-related terms, the most frequent lexemes reflected recovery motivation and progress (e.g., \u0026ldquo;recover,\u0026rdquo; \u0026ldquo;rehabilitation\u0026rdquo;). Negative posts accounted for 22.9% (115 posts), and neutral posts were the least common (20.1%, 101 posts). For both negative and neutral categories, high-frequency words were primarily symptom-focused (e.g., \u0026ldquo;binge eating,\u0026rdquo; \u0026ldquo;purging,\u0026rdquo; \u0026ldquo;weight\u0026rdquo;) (\u003cb\u003eFigures S2\u0026ndash;S3\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e3.1.3 LDA Topic Analysis\u003c/h2\u003e \u003cp\u003eThrough LDA modeling, three distinct thematic clusters were identified in content creators\u0026rsquo; posts (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The number of three clusters was selected because it achieved a favorable balance between low perplexity and high topic coherence, yielding thematically distinct, human-interpretable topics suitable for psychologically meaningful inference and monitoring (\u003cb\u003eTable S1\u003c/b\u003e). Topic 1, \u003cem\u003eEmotional Struggles and Meaning-Making around EDs\u003c/em\u003e, included emotional distress surrounding self-reported EDs and captured emotional distress related to self-reported EDs, including weight-loss efforts, depression and anxiety, and worries about body shape and health in everyday life. It depicted an ongoing search for meaning as individuals try to understand and live with self-reported EDs. Topic 2, \u003cem\u003eMale Binge\u0026ndash;Purge Episodes and Self-Rescue Attempts\u003c/em\u003e, centered on binge\u0026ndash;purge experiences and subsequent \u0026ldquo;self-rescue\u0026rdquo; efforts, such as describing episodes of binge eating and purging and then setting rules or plans to regain control. Topic 3, \u003cem\u003eJournaling Treatment, Control, and Recovery Journeys\u003c/em\u003e, reflected the use of posts as a recovery journal, including narratives about hospital admission and discharge, struggles with control over food, eating, and weight, and ongoing efforts to work toward recovery.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLDA modeling of posts\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLabels\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTerms\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmotional Struggles and Meaning-Making around EDs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eweight loss, depression, search, loss, need, eating, anorexia, everyone, at school, health, disorder, life, ED sufferers, anxiety, advice, body shape, develop, calculation, recovery, calories, as, see, diet, food, self-rescue, eat meals, guide, world, logic, underlying\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale Binge\u0026ndash;Purge Episodes and Self-Rescue Attempts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ebinge eating, boys, vomiting/purging, recording, milk tea, self-rescue, be able to, food, dinner, come out, height, give up, dinner, drinks, little boy, binge episode, stop binging, self-help, bravely face, effort, hold back, guide, avoid, appearance, cannot, anxiety, story, weight, share, anorexia nervosa\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJournaling Treatment, Control, and Recovery Journeys\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eeating, disorder, topics, rehabilitation, recovery, binge eating, appetite, vomiting/purging, anorexia nervosa, diet, weight loss, reflection, compulsion, food, weight, hospital admission, stability, time, calories, discharge from hospital, exercise, cannot, control, fear, meaning, unable to stop, walk out, method, change, everyone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e3.1.4 Word Cloud and Frequency Analysis\u003c/h2\u003e \u003cp\u003eWord cloud and frequency analyses (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u0026amp; \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) showed that content creators\u0026rsquo; posts centered heavily on terms directly related to self-reported ED behaviors and recovery, such as \u0026ldquo;eating/eat,\u0026rdquo; \u0026ldquo;disorder,\u0026rdquo; \u0026ldquo;binge eating,\u0026rdquo; \u0026ldquo;purging,\u0026rdquo; \u0026ldquo;rehabilitation,\u0026rdquo; and \u0026ldquo;recovery.\u0026rdquo; Also, the frequent appearance of \u0026ldquo;male/boy [男/男生]\u0026rdquo; suggested that the content creator actively positions their experiences within the context of male identity. High-frequency use of verbs such as \u0026ldquo;quit,\u0026rdquo; \u0026ldquo;control,\u0026rdquo; \u0026ldquo;record,\u0026rdquo; and \u0026ldquo;recover\u0026rdquo; further indicated that the platform was used not only for emotional disclosure but also for self-monitoring and behavior tracking.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Public Comments\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1. Sentence-Level Descriptive Analysis of Comments\u003c/h2\u003e \u003cp\u003eDescriptive analysis of 20,844 comments showed that the length of comment texts ranged from 1 to 300 characters, with a mean of 24.61 characters and a relatively large standard deviation of 30.19. The 25th, 50th, and 75th percentiles are 8, 15, and 29 characters, respectively, indicating that while many comments fall within a moderately short range, there were a few instances where the content is relatively longer, resulting in significant variability and a noticeable right tail. Short comments with no more than 10 characters accounted for 33.5% of the sample, whereas long comments with 30 characters or more accounted for 23.9%.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2 Sentiment Analysis of Public Comments\u003c/h2\u003e \u003cp\u003eSentiment analysis of public comments (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) similarly revealed a mixed emotional profile, χ\u0026sup2;(2)\u0026thinsp;=\u0026thinsp;1359.7, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001. Nearly half of the comments (48.1%) were positive. Word-frequency analysis showed that, in addition to eating/weight-related terms, frequent positive words included expressions of encouragement and empathy (e.g., \u0026ldquo;keep going,\u0026rdquo; \u0026ldquo;good\u0026rdquo;) (\u003cb\u003eFigure S4\u003c/b\u003e). Negative comments accounted for 34.5%, and neutral comments accounted for 17.3%. For both negative and neutral sentiment categories, the most frequent words were primarily related to eating and body image concerns (\u003cb\u003eFigures S5\u0026ndash;S6\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e3.2.3 LDA Topic Analysis of Comments\u003c/h2\u003e \u003cp\u003eLDA topic modeling identified three thematic clusters within public comments (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Also, the number of three thematic clusters was selected because it maximized thematic diversity and maintained high topic exclusivity, with only negligible changes in perplexity relative to adjacent solutions (\u003cb\u003eTable S2\u003c/b\u003e). Topic 1, \u003cem\u003eBody Image- and Eating-Related Communication\u003c/em\u003e, comprised interpersonal exchanges focused on appearance, eating, and food-related experiences. Comments frequently referred to the commenter\u0026rsquo;s own weight, food intake, and exercise routines, shared similar struggles, and posed questions to the blogger about their eating, strategies, or symptoms. Topic 2, \u003cem\u003eEmpathic Care and Psychological Support\u003c/em\u003e, centered on recovery-oriented messages, including expressions of empathy, encouragement, and psychological support (e.g., \u0026ldquo;keep going,\u0026rdquo; \u0026ldquo;cheer up,\u0026rdquo; or the Chinese term \u0026ldquo;孩子\u0026rdquo; [child], used in a caring way to convey warmth and concern), often urging content creators to persist with self-care. Topic 3, \u003cem\u003eMale Body Ideals and Appearance Judgments\u003c/em\u003e, captured comments that evaluated the content creators\u0026rsquo; body weight/shape and attractiveness in relation to male body ideals (e.g., height, muscularity, too thin, fitness, and strength), often accompanied by prescriptive appearance-related suggestions such as gaining muscle, changing weight, or increasing fitness.\u003c/p\u003e \u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLDA modeling of comments\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eID\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003elabels\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eterms\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eBody Image- and Eating-Related Communication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003enow, body weight, exactly, but, feeling, myself, binge eating, still, every day, lose weight, no, normal, body, food, can, time, how many, physical activity, not, can\u0026apos;t, what, in this way, calories, eat, teacher, appetite, start, a day, how\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eEmpathic Care and Psychological Support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003ereally, oneself, keep going, certainly, think, properly, already, health, child, wish, cheer up, thanks, recovery, such, us, these, slowly, life, more and more, condition, notice, why, unable, psychology, can, watch, possible, love, therefore, require\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMale Body Ideals and Appearance Judgments\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003ebody weight, this, should, may, height, if so, a bit, male, if, excuse me, suggestion, an, muscle, nice, aerobic exercise, female, fat loss, too thin, like, kilogram, suitable, check, hospital, fitness, muscle gain, laugh, lose weight again, strength, require, relatively\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003ch2\u003e3.2.4 Word Cloud and Frequency Analysis of Comments\u003c/h2\u003e\n\u003cp\u003eWord cloud and frequency analyses of comments (Figs. \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e \u0026amp; \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) revealed highly interactive and evaluative language use. High-frequency words such as \u0026ldquo;eat,\u0026rdquo; \u0026ldquo;good,\u0026rdquo; \u0026ldquo;weight,\u0026rdquo; \u0026ldquo;not,\u0026rdquo; and terms associated with purging/vomiting indicate that commenters focused heavily on body image- and eating-related concerns, often directing feedback toward the content creators\u0026rsquo; actions rather than simply observing them. Positive expressions (e.g., \u0026ldquo;keep up\u0026rdquo;) reflected interactive, supportive responses, whereas evaluative terms such as \u0026ldquo;weight,\u0026rdquo; \u0026ldquo;fat,\u0026rdquo; and \u0026ldquo;thin\u0026rdquo; suggested ongoing monitoring, judgment, or pressure related to body size and control.\u003c/p\u003e\n"},{"header":"4. Discussion","content":"\u003cp\u003eDrawing on posts by male content creators with self-reported EDs and related public comments on the Chinese social media platform, Xiaohongshu, this study examined how this population discloses the ED experiences on Xiaohongshu and how the public responds, using sentiment analysis and topic modeling of 502 posts and 20,844 comments. Across both posts and comments, emotional expression was mixed but predominantly positive. The findings align with previous studies suggesting that social media can serve as an outlet for illness communication while simultaneously eliciting feedback[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. The findings extend our understanding of male self-reported ED experiences in the Chinese context by situating them within a naturalistic, interactive digital environment.\u003c/p\u003e \u003cp\u003eAlthough male self-reported ED content creators described profound emotional struggles associated with their self-reported EDs, positive sentiment was the dominant emotional tone. Posts frequently contained messages of hope, perseverance, and commitment to incremental recovery goals. Topic modeling further showed that content creators used the platform not only to describe their symptoms but also to engage in meaning-making around self-reported EDs, as well as to self-encourage and monitor their behaviors by documenting recovery efforts. The practices are plausibly driven by attempts to satisfy basic psychological needs for autonomy, competence, and relatedness[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Meanwhile, the theme we labeled \u003cem\u003eMale Binge\u0026ndash;Purge Episodes and Self-Rescue Attempts\u003c/em\u003e revealed detailed narratives of binge eating and purging, followed by self-help efforts. These narratives showed shifts between intense shame and self-blame and deliberate self-coaching and crisis-management strategies, indicating rapid emotional changes surrounding binge\u0026ndash;purge episodes. Such fluctuations may contribute to the maintenance of the binge\u0026ndash;purge cycle, consistent with prior findings that negative affect intensifies before binge eating and purging and decreases afterward, alongside corresponding changes in positive affect [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePublic responses were mixed but predominantly positive, often offering emotional reassurance and encouragement for recovery. LDA analysis of comments revealed three coexisting themes: \u003cem\u003eEmpathic Care and Psychological Support\u003c/em\u003e; \u003cem\u003eBody Image and Eating-Related Communication\u003c/em\u003e; and \u003cem\u003eMale Body Ideals and Appearance Judgments\u003c/em\u003e. The first theme captured warm, affiliative exchanges (e.g., expressions of comfort and encouragement), whereas the latter two were dominated by appearance- and eating-focused talk. Commenters evaluated the content creators\u0026rsquo; body size, weight, and attractiveness, shared their own eating and exercise experiences, and sometimes proposed specific strategies for changing weight, shape, or muscularity. The coexistence of encouragement and male-identity-based body image comments and judgments highlights that male self-reported ED disclosures are embedded within broader norms about what an idealized male body should look like (e.g., being tall, muscular, and strong rather than \u0026ldquo;too thin\u0026rdquo;). In this context, commenters simultaneously affirm and police men\u0026rsquo;s bodies through references to height, muscularity, and fitness. This blurred the boundary between support and surveillance and reinforced sex/gender-specific appearance pressures and body ideals. The pattern suggests that although social media can serve as a platform for support and facilitate connection and open communication, it also reproduces broader sociocultural pressures around body ideals and \u0026ldquo;unhealthy\u0026rdquo; eating/weight coping strategies[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Thus, social media becomes not only a site of support but also a site where norms about how the \u0026ldquo;ideal body\u0026rdquo; should look and behave are monitored and reinforced[\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBy applying computational analysis to naturalistic social media data, this study demonstrates that digital platforms can provide meaningful insight into how males experience and negotiate self-reported EDs and related public feedback. First, the predominance of positive sentiment in both posts and comments suggests that social media may serve as a source of informal, peer-based support, with public posting functioning as self-monitoring and positive reinforcement of recovery behaviors. Second, as warm and encouraging responses frequently coexist with body image- and eating-related communication and male-identity-based comments and judgments, the masculine norms can mask and normalize potentially harmful feedback. There is therefore a need for sex/gender-sensitive intervention strategies that explicitly acknowledge how masculine norms (e.g., strength, discipline, control, muscularity) shape both self-perception and the feedback received from others. For example, social media platforms can implement platform-supported warning that adds contextual health information to user-generated content, encouraging critical evaluation of potentially harmful social stigma. Third, because comment content frequently reflects weight- and shape-focused surveillance and communicates disordered eating and compensatory behaviors (e.g., binge eating, restriction, purging), platforms could use strategies to detect and flag or filter high-risk content[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] and prompt users toward evidence-based and safe resources.\u003c/p\u003e \u003cp\u003eThis study has limitations that offer directions for future research. First, the present study focused on a single social media platform and a limited sample of content creators. The relatively small dataset may limit the diversity of experiences, narrative styles, and emotional expressions captured. The identified topics and sentiment patterns may disproportionately reflect the perspectives of the subset of highly active users. The generalizability of the finding to other platforms or populations is therefore constrained. Models may also misclassify sentiment when expressions rely on sarcasm, metaphor, or culturally embedded meanings, leading to an inaccurate representation of some emotional signals. Additionally, the cross-sectional design limits inference about temporal change or causal effects of feedback. Future research should examine longitudinal posting dynamics (e.g., whether shifts in sentiment predict relapse or recovery) and integrate multimodal content (e.g., images and engagement metrics) to further explore the media disclosure of male EDs. Furthermore, among sexual minoritized men in China, eating and body image problems are closely associated with sexual self-labelling and gender expression[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. This indicates the importance of incorporating comparison groups based on gender and sexual orientation when examining intersecting forms of stigma. Finally, although we focused on males with self-reported EDs, our search strategy targeted traditional self-reported EDs and did not explicitly include muscularity-oriented disordered eating (e.g., muscle dysmorphia, compulsive bulking/cutting, or anabolic-androgenic steroid use), which may be particularly salient and risky for males[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Future studies should explicitly capture these muscularity-related presentations and leverage social media data to develop platform-based detection, prevention, and intervention strategies tailored to muscularity-oriented disordered eating[\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOverall, this study used sentiment analysis and topic modeling to characterize how males with self-reported EDs discuss their experiences and how viewers comment on those experiences. Emotional expression in both posts and comments was mixed yet predominantly positive, indicating that social media can function as a space for recovery-oriented self-expression and informal support. At the same time, public responses often paired encouragement with muscularity-oriented appearance commentary that promoted culturally salient male body ideals that centered on muscularity, height, and strength. The online community\u0026rsquo;s simultaneous promotion of warm support and norms about how the ideal body should look reinforced narrow male body ideals and normalized disordered eating and compensatory behaviors. These findings highlight the need for sex/gender-sensitive, platform-supported strategies that harness the supportive potential of social media while mitigating its risks.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cem\u003eED\u003c/em\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEating disorders\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cem\u003eLDA\u003c/em\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLatent Dirichlet Allocation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo potential conflict of interest was reported by the author(s).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJinbo He was supported by the National Natural Science Foundation of China (Grant Number 72204208) and the 2022 Shenzhen College Stability Support Plan from the Shenzhen Science and Technology Innovation Commission (2022年度深圳市稳定支持计; Grant No. 2023SC0028).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eShaojie Yang: Formal Analysis, Writing \u0026ndash; original draft, and Writing\u0026ndash;review \u0026amp; editing. Sanle Zhao: Writing \u0026ndash; original draft, and Writing\u0026ndash;review \u0026amp; editing. Wesley R. Barnhart: Writing \u0026ndash; original draft, and Writing\u0026ndash;review \u0026amp; editing. Peiyi Wang: Writing \u0026ndash; original draft, and Writing\u0026ndash;review \u0026amp; editing.\u0026nbsp;Yunyi Cheng: Writing\u0026ndash;review \u0026amp; editing. Bijie Tie: Writing\u0026ndash;review \u0026amp; editing. Feng Ji: Supervision, and Writing\u0026ndash;review \u0026amp; editing. Jinbo He: Conceptualization, Supervision, Funding acquisition, Writing \u0026ndash; original draft, and Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe project was approved by the Institutional Review Board (Applied Psychology) of The Chinese University of Hong Kong, Shenzhen (No. EF20220809001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThese data are available from the corresponding author upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of generative AI in scientific writing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the preparation of this work, the authors utilized GPT-5 to enhance the language of the manuscript. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the content of the published article.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e\u0026Aacute;gh T, Kov\u0026aacute;cs G, Supina D, Pawaskar M, Herman BK, Vok\u0026oacute; Z, Sheehan DV. A systematic review of the health-related quality of life and economic burdens of anorexia nervosa, bulimia nervosa, and binge eating disorder. Eating and Weight Disorders-Studies on Anorexia. Bulimia Obes. 2016;21(3):353\u0026ndash;64. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s40519-016-0264-x\u003c/span\u003e\u003cspan address=\"10.1007/s40519-016-0264-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConti C, Lanzara R, Scipioni M, Iasenza M, Guagnano MT, Fulcheri M. The relationship between binge eating disorder and suicidality: a systematic review. Front Psychol. 2017;8:2125. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpsyg.2017.02125\u003c/span\u003e\u003cspan address=\"10.3389/fpsyg.2017.02125\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrown TA, Keel PK. Eating Disorders in Boys and Men. Ann Rev Clin Psychol. 2023;19:177\u0026ndash;205. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1146/annurev-clinpsy-080921-074125\u003c/span\u003e\u003cspan address=\"10.1146/annurev-clinpsy-080921-074125\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStrother E, Lemberg R, Stanford SC, Turberville D. Eating disorders in men: underdiagnosed, undertreated, and misunderstood. Eat Disord. 2012;20(5):346\u0026ndash;55. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/10640266.2012.715512\u003c/span\u003e\u003cspan address=\"10.1080/10640266.2012.715512\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCalzo JP, Horton NJ, Sonneville KR, Swanson SA, Crosby RD, Micali N, Eddy KT, Field AE. Male Eating Disorder Symptom Patterns and Health Correlates From 13 to 26 Years of Age. J Am Acad Child Adolesc Psychiatry. 2016;55(8):693\u0026ndash;e7002. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jaac.2016.05.011\u003c/span\u003e\u003cspan address=\"10.1016/j.jaac.2016.05.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBentley C, Mond J, Rodgers B. Sex differences in psychosocial impairment associated with eating-disordered behavior: What if there aren't any? Eat Behav. 2014;15(4):609\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.eatbeh.2014.08.015\u003c/span\u003e\u003cspan address=\"10.1016/j.eatbeh.2014.08.015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMitchison D, Mond J. Epidemiology of eating disorders, eating disordered behaviour, and body image disturbance in males: a narrative review. J Eat Disorders. 2015;3(1):20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s40337-015-0058-y\u003c/span\u003e\u003cspan address=\"10.1186/s40337-015-0058-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIwajomo T, Bondy SJ, de Oliveira C, Colton P, Trottier K, Kurdyak P. Excess mortality associated with eating disorders: population-based cohort study. Br J Psychiatry. 2021;219(3):487\u0026ndash;93. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1192/bjp.2020.197\u003c/span\u003e\u003cspan address=\"10.1192/bjp.2020.197\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLavender JM, Brown TA, Murray SB. Men, muscles, and eating disorders: an overview of traditional and muscularity-oriented disordered eating. Curr Psychiatry Rep. 2017;19(6):32. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11920-017-0787-5\u003c/span\u003e\u003cspan address=\"10.1007/s11920-017-0787-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNagata JM, Murray SB, Bibbins-Domingo K, Garber AK, Mitchison D, Griffiths S. Predictors of muscularity‐oriented disordered eating behaviors in US young adults: A prospective cohort study. Int J Eat Disord. 2019;52(12):1380\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/eat.23094\u003c/span\u003e\u003cspan address=\"10.1002/eat.23094\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHolder K. Eating Disorder Hospitalizations in the United States: Insights and Implications from the National Inpatient Sample [Doctoral dissertation, Johns Hopkins University]. Johns Hopkins University. 2025. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://jscholarship.library.jhu.edu/handle/1774.2/70761\u003c/span\u003e\u003cspan address=\"https://jscholarship.library.jhu.edu/handle/1774.2/70761\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGorrell S, Murray SB. Eating disorders in males. Child and Adolescent Psychiatric Clinics of North America. 2019;28(4):641. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.chc.2019.05.012\u003c/span\u003e\u003cspan address=\"10.1016/j.chc.2019.05.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGriffiths S, Mond JM, Murray SB, Touyz S. The prevalence and adverse associations of stigmatization in people with eating disorders. Int J Eat Disord. 2015;48(6):767\u0026ndash;74. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/eat.22353\u003c/span\u003e\u003cspan address=\"10.1002/eat.22353\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGriffiths S, Mond JM, Murray SB, Touyz S. Young peoples' stigmatizing attitudes and beliefs about anorexia nervosa and muscle dysmorphia. Int J Eat Disord. 2014;47(2):189\u0026ndash;95. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/eat.22220\u003c/span\u003e\u003cspan address=\"10.1002/eat.22220\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMacLean A, Sweeting H, Walker L, Patterson C, R\u0026auml;is\u0026auml;nen U, Hunt K. It's not healthy and it's decidedly not masculine: a media analysis of UK newspaper representations of eating disorders in males. BMJ Open. 2015;5(5):e007468. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmjopen-2014-007468\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2014-007468\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLehe MS, Halbeisen G, Juergensen VC, Sabel L, Steins-Loeber S, Paslakis G. Boys don\u0026rsquo;t try? Gendered stigma specifically reduces help-seeking for disordered eating in men, but not women. J Eat Disorders. 2025;13(1):1\u0026ndash;15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s40337-025-01407-7\u003c/span\u003e\u003cspan address=\"10.1186/s40337-025-01407-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRichardson C, Paslakis G. Men\u0026rsquo;s experiences of eating disorder treatment: A qualitative systematic review of men-only studies. J Psychiatr Ment Health Nurs. 2021;28(2):237\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/jpm.12670\u003c/span\u003e\u003cspan address=\"10.1111/jpm.12670\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMurray SB, Griffiths S, Nagata JM. Community-based eating disorder research in males: a call to action. J Adolesc Health. 2018;62(6):649\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jadohealth.2018.03.008\u003c/span\u003e\u003cspan address=\"10.1016/j.jadohealth.2018.03.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMurray SB, Griffiths S, Lavender JM. Introduction to a special issue on eating disorders and related symptomatology in male populations. Int J Eat Disord. 2019;52(12):1339\u0026ndash;42. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/eat.23184\u003c/span\u003e\u003cspan address=\"10.1002/eat.23184\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTong J, Miao SJ, Wang J, Zhang JJ, Wu HM, Li T, Hsu LG. Five cases of male eating disorders in Central China. Int J Eat Disord. 2005;37(1):72\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/eat.20061\u003c/span\u003e\u003cspan address=\"10.1002/eat.20061\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen ZF, et al. The prevalence of anorexia nervosa and bulimia nervosa among freshman medical college students in China. Int J Eat Disord. 1992;12(2):209\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/1098-108X(199209)12:2%3C209::AID-EAT2260120210%3E3.0.CO;2-%23\u003c/span\u003e\u003cspan address=\"10.1002/1098-108X(199209)12:2%3C209::AID-EAT2260120210%3E3.0.CO;2-%23\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen H, Jackson T. Prevalence and sociodemographic correlates of eating disorder endorsements among adolescents and young adults from China. Eur Eat Disorders Rev. 2008;16(5):375\u0026ndash;85. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/erv.837\u003c/span\u003e\u003cspan address=\"10.1002/erv.837\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePike KM, Dunne PE. The rise of eating disorders in Asia: a review. J Eat Disorders. 2015;3(1):33. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s40337-015-0070-2\u003c/span\u003e\u003cspan address=\"10.1186/s40337-015-0070-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRobinson KJ, Mountford VA, Sperlinger DJ. Being men with eating disorders: Perspectives of male eating disorder service-users. J Health Psychol. 2013;18(2):176\u0026ndash;86. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/1359105312440298\u003c/span\u003e\u003cspan address=\"10.1177/1359105312440298\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDarcy AM, Lin IHJ. Are we asking the right questions? A review of assessment of males with eating disorders. Eat Disord. 2012;20(5):416\u0026ndash;26. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/10640266.2012.715521\u003c/span\u003e\u003cspan address=\"10.1080/10640266.2012.715521\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMurray SB, Nagata JM, Griffiths S, Calzo JP, Brown TA, Mitchison D, Blashill JA, Mond JM. The enigma of male eating disorders: A critical review and synthesis. Clin Psychol Rev. 2017;57:1\u0026ndash;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.cpr.2017.08.001\u003c/span\u003e\u003cspan address=\"10.1016/j.cpr.2017.08.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChapman J, Woodman T. Disordered eating in male athletes: a meta-analysis. J Sports Sci. 2016;34(2):101\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/02640414.2015.1040824\u003c/span\u003e\u003cspan address=\"10.1080/02640414.2015.1040824\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCavazos-Rehg PA, Krauss MJ, Costello SJ, Kaiser N, Cahn ES, Fitzsimmons-Craft EE, Wilfley DE. I just want to be skinny.: A content analysis of tweets expressing eating disorder symptoms. PLoS ONE. 2019;14(1):e0207506. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0207506\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0207506\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoessner M, Feldhege J, Wolf M, Bauer S. Analyzing big data in social media: Text and network analyses of an eating disorder forum. Int J Eat Disord. 2018;51(7):656\u0026ndash;67. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/eat.22878\u003c/span\u003e\u003cspan address=\"10.1002/eat.22878\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang T, Brede M, Ianni A, Mentzakis E. Social interactions in online eating disorder communities: A network perspective. PLoS ONE. 2018;13(7):e0200800. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0200800\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0200800\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBickerstaff JM, Karim S, Whitman RK, Cypher A, Wiener S, Radovic A. You have people here to help you, people like me: A qualitative analysis of a blogging intervention for adolescents and young adults with depression or anxiety. J Technol Behav Sci. 2021;6(4):578\u0026ndash;88. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s41347-021-00210-w\u003c/span\u003e\u003cspan address=\"10.1007/s41347-021-00210-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrescott J, Rathbone AL, Brown G. Online peer to peer support: Qualitative analysis of UK and US open mental health Facebook groups. Digit Health. 2020;6:2055207620979209. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/2055207620979209\u003c/span\u003e\u003cspan address=\"10.1177/2055207620979209\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStrobel CB, Lennon J. Men in online eating disorder recovery spaces: Gendered barriers, content moderation, and narrative experimentation. Sociol Compass. 2023;17(11):e13156. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/soc4.13156\u003c/span\u003e\u003cspan address=\"10.1111/soc4.13156\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRounsefell K, Gibson S, McLean S, Blair M, Molenaar A, Brennan L, Truby H, McCaffrey TA. Social media, body image and food choices in healthy young adults: A mixed methods systematic review. Nutr Dietetics. 2020;77(1):19\u0026ndash;40. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/1747-0080.12581\u003c/span\u003e\u003cspan address=\"10.1111/1747-0080.12581\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMerino M, Tornero-Aguilera JF, Rubio-Zarapuz A, Villanueva-Tobaldo CV, Mart\u0026iacute;n-Rodr\u0026iacute;guez A, Clemente-Su\u0026aacute;rez VJ. Body Perceptions and Psychological Well-Being: A Review of the Impact of Social Media and Physical Measurements on Self-Esteem and Mental Health with a Focus on Body Image Satisfaction and Its Relationship with Cultural and Gender Factors. Healthcare. 2024;12(14):1396. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/healthcare12141396\u003c/span\u003e\u003cspan address=\"10.3390/healthcare12141396\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLonergan AR, Mitchison D, Bussey K, Fardouly J. Social media and eating and body image concerns among men and boys. Eating Disorders in Boys and Men. https://doi: Springer, Cham; 2021. pp. 307\u0026ndash;16. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/978-3-030-67127-3_20\u003c/span\u003e\u003cspan address=\"10.1007/978-3-030-67127-3_20\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMalova E, Dunleavy V. Men have eating disorders too: An analysis of online narratives posted by men with eating disorders on YouTube. Eat Disord. 2022;30(4):437\u0026ndash;52. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/10640266.2021.1930338\u003c/span\u003e\u003cspan address=\"10.1080/10640266.2021.1930338\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRana TA, Cheah YN, Letchmunan S. Topic modeling in sentiment analysis: A systematic review. J ICT Res Appl. 2016;10(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5614/itbj.ict.res.appl.2016.10.1.6\u003c/span\u003e\u003cspan address=\"10.5614/itbj.ict.res.appl.2016.10.1.6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJeong B, Yoon J, Lee JM. Social media mining for product planning: A product opportunity mining approach based on topic modeling and sentiment analysis. Int J Inf Manag. 2019;48:280\u0026ndash;90. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ijinfomgt.2017.09.009\u003c/span\u003e\u003cspan address=\"10.1016/j.ijinfomgt.2017.09.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMelton CA, Olusanya OA, Ammar N, Shaban-Nejad A. Public sentiment analysis and topic modeling regarding COVID-19 vaccines on the Reddit social media platform: A call to action for strengthening vaccine confidence. J Infect Public Health. 2021;14(10):1505\u0026ndash;12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jiph.2021.08.010\u003c/span\u003e\u003cspan address=\"10.1016/j.jiph.2021.08.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang T, Schoene AM, Ji S, Ananiadou S. Natural language processing applied to mental illness detection: a narrative review. NPJ Digit Med. 2022;5(1):46. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41746-022-00589-7\u003c/span\u003e\u003cspan address=\"10.1038/s41746-022-00589-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim Y, R\u0026ouml;mer-Barron U. Detection and Analysis of Depression-Related Language in an Online Community: Machine Learning, Topic Modeling, and Corpus-Linguistic Approaches. Corpus-based Studies across Humanities. 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1515/csh-2025-0005\u003c/span\u003e\u003cspan address=\"10.1515/csh-2025-0005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSpinczyk D, Nabrdalik K, Rojewska K. Computer aided sentiment analysis of anorexia nervosa patients\u0026rsquo; vocabulary. Biomed Eng Online. 2018;17(1):19. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12938-018-0451-2\u003c/span\u003e\u003cspan address=\"10.1186/s12938-018-0451-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOksanen A, Garcia D, Sirola A, N\u0026auml;si M, Kaakinen M, Keipi T, R\u0026auml;s\u0026auml;nen P. Pro-anorexia and anti-pro-anorexia videos on YouTube: Sentiment analysis of user responses. J Med Internet Res. 2015;17(11):e256. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2196/jmir.5007\u003c/span\u003e\u003cspan address=\"10.2196/jmir.5007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou S, Zhao Y, Bian J, Haynos AF, Zhang R. Exploring eating disorder topics on Twitter: machine learning approach. JMIR Med Inf. 2020;8(10):e18273. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2196/18273\u003c/span\u003e\u003cspan address=\"10.2196/18273\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZunic A, Corcoran P, Spasic I. Sentiment analysis in health and well-being: systematic review. JMIR Med Inf. 2020;8(1):e16023. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2196/16023\u003c/span\u003e\u003cspan address=\"10.2196/16023\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu Y, Shan Y, Sun S, Ji M, Zhou S, You Y, Liu H, Shen Y. Topic modeling and content analysis of people\u0026rsquo;s anxiety-related concerns raised on a computer-mediated health platform. Sci Rep. 2024;14(1):27520. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-024-79164-x\u003c/span\u003e\u003cspan address=\"10.1038/s41598-024-79164-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLang M, Chen P, Li X, Ye Y. Refusing appearance anxiety: A content analysis of body positive posts on Chinese social media. Body Image. 2023;45:414\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.bodyim.2023.04.002\u003c/span\u003e\u003cspan address=\"10.1016/j.bodyim.2023.04.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang C. Body Image and Social Media in China: Examining Body Image Discourses among Young Chinese Women on the Xiaohongshu Platform. J Int Crisis Risk Communication Res. 2024;7:1193\u0026ndash;200. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.63278/jicrcr.vi.2198\u003c/span\u003e\u003cspan address=\"10.63278/jicrcr.vi.2198\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang J. The Impact of Pamela\u0026rsquo;s Fitness Content on Xiaohongshu on Women\u0026rsquo;s Body Anxiety: An Analysis of Visual Narrative and Emotion Mobilization. Literature Lang Cult Stud. 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.63313/LLCS.2006\u003c/span\u003e\u003cspan address=\"10.63313/LLCS.2006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArseniev-Koehler A, Lee H, McCormick T, Moreno MA, #Proana. Pro\u0026ndash;eating disorder socialization on Twitter. J Adolesc Health. 2016;58(6):659\u0026ndash;64. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jadohealth.2016.02.012\u003c/span\u003e\u003cspan address=\"10.1016/j.jadohealth.2016.02.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSukunesan S, Huynh M, Sharp G. Examining the Pro-Eating Disorders Community on Twitter Via the Hashtag #proana: Statistical Modeling Approach. JMIR Mental Health. 2021;8(7):e24340. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2196/24340\u003c/span\u003e\u003cspan address=\"10.2196/24340\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eisnowfy. snownlp: Python library for processing Chinese text [Computer software]. GitHub. n.d. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/isnowfy/snownlp\u003c/span\u003e\u003cspan address=\"https://github.com/isnowfy/snownlp\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAu ES, Cosh SM. Social media and eating disorder recovery: An exploration of Instagram recovery community users and their reasons for engagement. Eat Behav. 2022;46:101651. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.eatbeh.2022.101651\u003c/span\u003e\u003cspan address=\"10.1016/j.eatbeh.2022.101651\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi J, Tang L. I Want to Hold an Umbrella Over You Because I Have Been in the Rain: Exploring Patient Influencers\u0026rsquo; Motivations to Share Eating Disorders Experiences from a Self-Determination Theory Perspective. Health Commun. 2025;40(11):2228\u0026ndash;39. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/10410236.2024.2447103\u003c/span\u003e\u003cspan address=\"10.1080/10410236.2024.2447103\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarris EA, Moeck EK, Griffiths S. Affective Trajectories of Binge Eating, Purging, and Exercise Among Sexual Minority Men. Int J Eat Disord. 2025;58(5):939\u0026ndash;51. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/eat.24406\u003c/span\u003e\u003cspan address=\"10.1002/eat.24406\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLogrieco G, Marchili MR, Roversi M, Villani A. The Paradox of TikTok Anti-Pro-Anorexia Videos: How Social Media Can Promote Non-Suicidal Self-Injury and Anorexia. Int J Environ Res Public Health. 2020;18(3):1041. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph18031041\u003c/span\u003e\u003cspan address=\"10.3390/ijerph18031041\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStrobel CB. The shadow that hovered over: Gender salience in eating disorder recovery. Gend Issues. 2022;39(3):368\u0026ndash;86. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s12147-022-09294-x\u003c/span\u003e\u003cspan address=\"10.1007/s12147-022-09294-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDiSalvo LM, Saenz GV, Wong WE, Li D. Social Media Safety Practices and flagging sensitive posts. In: 2022 IEEE 22nd International Conference on Software Quality, Reliability, and, Companion S. (QRS-C); 2022. IEEE; 2022. pp. 8\u0026ndash;15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1109/QRS-C57518.2022.00012\u003c/span\u003e\u003cspan address=\"10.1109/QRS-C57518.2022.00012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePodorozhniak A, Oliinyk V, Liubchenko N. Strategies for Filtering Unwanted Comments in Social Media. In: 2024 IEEE 5th KhPI Week on Advanced Technology (KhPIWeek); 2024. IEEE; 2024. pp. 1\u0026ndash;4. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1109/KhPIWeek61434.2024.10877962\u003c/span\u003e\u003cspan address=\"10.1109/KhPIWeek61434.2024.10877962\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarnhart WR, Han J, Zhang Y, Luo W, Li Y, He J. Differences in Thinness-and Muscularity-Oriented Eating and Body Image Disturbances and Psychosocial Well-Being in Chinese Sexual Minority Men Reporting Top, Bottom, and Versatile Sexual Self-Labels. Arch Sex Behav. 2024;53(10):3973\u0026ndash;91. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10508-024-02962-x\u003c/span\u003e\u003cspan address=\"10.1007/s10508-024-02962-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMurray SB, Griffiths S, Mond JM. Evolving eating disorder psychopathology: Conceptualising muscularity-oriented disordered eating. Br J Psychiatry. 2016;208(5):414\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1192/bjp.bp.115.168427\u003c/span\u003e\u003cspan address=\"10.1192/bjp.bp.115.168427\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHe J, Ji F. Artificial intelligence and social media for the detection of eating disorders. Int J Eat Disord. 2025;58(7):1187\u0026ndash;90. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/eat.24438\u003c/span\u003e\u003cspan address=\"10.1002/eat.24438\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-eating-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"joed","sideBox":"Learn more about [Journal of Eating Disorders](http://jeatdisord.biomedcentral.com)","snPcode":"40337","submissionUrl":"https://submission.nature.com/new-submission/40337/3","title":"Journal of Eating Disorders","twitterHandle":"@JEatDisord","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"eating disorders, men, males, social media, sentiment analysis, topic modeling","lastPublishedDoi":"10.21203/rs.3.rs-9156420/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9156420/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMales with eating disorders (EDs) remain overlooked, particularly due to gendered stereotypes that characterize EDs as primarily affecting females. Social media provides a naturalistic context in which content creators disclose illness experiences and receive public feedback. This study used computational text analysis to examine how male ED experiences are discussed on Xiaohongshu (Little Red Note), a major Chinese social media platform.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe collected 502 posts from eight male self-reported ED content creators and 20,844 associated public comments posted between October 2021 and June 2025. In posts and comments, sentiment analysis was used to quantify emotional polarity (positive, neutral, negative), and latent Dirichlet Allocation topic modeling was used to identify semantic patterns.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe posts were predominantly positive (57.0%), reflecting recovery motivation, while 22.9% expressed negative affect, and 20.1% were neutral. Three associated thematic categories were revealed:(1) \u003cem\u003eEmotional Struggles and Meaning-Making around EDs\u003c/em\u003e, (2) \u003cem\u003eMale Binge\u0026ndash;Purge Episodes and Self-Rescue Attempts\u003c/em\u003e, and (3) \u003cem\u003eJournaling Treatment, Control, and Recovery Journeys\u003c/em\u003e. Comments also showed mixed sentiment, with a majority of positive responses (48.1%), followed by negative (34.5%) and neutral (17.3%). Three themes appeared from the comments: (1) \u003cem\u003eBody Image- and Eating-related Communication\u003c/em\u003e, (2) \u003cem\u003eEmpathic Care and Psychological Support\u003c/em\u003e, and (3) \u003cem\u003eMale Body Ideals and Appearance Judgments\u003c/em\u003e.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eMale self-reported ED discourse on social media presents a mixed emotional landscape, yet positive sentiments reflect the majority of posts and comments. Computational analysis of naturalistic digital traces provides scalable insights into male self-reported EDs, underscoring the need for sex/gender-sensitive communication and platform-level strategies to support interventions.\u003c/p\u003e","manuscriptTitle":"Male Self-Reported Eating Disorders on Chinese Social Media: A Computational Analysis of Xiaohongshu Posts and Comments","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-26 16:52:31","doi":"10.21203/rs.3.rs-9156420/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"303524388924695410105191093431708489888","date":"2026-05-01T20:22:31+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-24T17:55:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-24T08:55:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-24T08:54:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Eating Disorders","date":"2026-03-18T08:03:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-eating-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"joed","sideBox":"Learn more about [Journal of Eating Disorders](http://jeatdisord.biomedcentral.com)","snPcode":"40337","submissionUrl":"https://submission.nature.com/new-submission/40337/3","title":"Journal of Eating Disorders","twitterHandle":"@JEatDisord","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1daad484-1a86-4267-b62d-b5931d37ecc8","owner":[],"postedDate":"March 26th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"303524388924695410105191093431708489888","date":"2026-05-01T20:22:31+00:00","index":53,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-26T16:52:31+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-26 16:52:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9156420","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9156420","identity":"rs-9156420","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}