{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T19:04:06Z","timestamp":1782846246899,"version":"3.54.5"},"reference-count":58,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Med Internet Res"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n YouTube, as a participatory platform, allows algorithmic curation and user engagement to shape health information flows. This dynamic amplifies and isolates harmful narratives, producing enclosed \u201crefracted publics.\u201d Pro-anorexia (pro-ana) content exemplifies this, glamorizing extreme thinness as self-control and promoting disordered eating while distancing viewers from evidence-based health discourse. Despite concerns about public health consequences, few studies have examined how channel characteristics and framing strategies drive engagement and echo chamber formation.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study analyzed how pro-ana discourse circulates on YouTube and identified entry points for intervention. It (1) compared pro-ana, anti\u2013pro-ana, and recovery frames by channel type (institutional vs individual) and subscriber scale (mega [\u22651,000,000], meso [100,000-999,999], or micro [10,000-99,999]); (2) constructed video-level networks from overlapping commenters to trace discourse clustering over time; and (3) evaluated how frame and channel attributes shape network connectivity and frame-crossing.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n We collected 489 Korean-language YouTube videos (January 2020-August 2024) using pro-ana keywords and related-video crawling. Each was coded into 3 frames. Channels were classified by operator type and subscriber scale. A weighted commenter-overlap network was built, backbone-extracted, and analyzed through social network analysis. An exponential random graph model tested predictors of intervideo ties.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Of 489 videos, 369 (75.5%) promoted pro-ana content, mostly in micro- and meso-individual channels (361\/369, 97.8%). Recovery frames appeared mainly in micro-individual channels (47\/52, 90%). Anti\u2013pro-ana frames clustered in institutional channels (46\/68, 68%) but remained structurally peripheral. After backbone filtering, the commenter-overlap network comprised 435 videos and 906 edges. The network showed low density (0.96%) and moderate modularity (0.58) with 19 communities, indicating a fragmented, echo chamber\u2013like structure. Longitudinally, density declined while modularity rose, consistent with echo-chamber intensification. The largest community (n=242) was predominantly pro-ana, while recovery-only (n=25) and anti\u2013pro-ana (n=13) communities were peripheral. The exponential random graph model revealed that homophily was strong for anti\u2013pro-ana (odds ratio [OR]=2.20;\n P<\/jats:italic>\n <.001) and became significant for pro-ana with channel\u00d7frame interactions (OR=3.12;\n P<\/jats:italic>\n <.001). Critically, recovery frames in meso-individual channels were associated with greater intervideo connectivity (OR=2.59;\n P<\/jats:italic>\n <.001), and anti\u2013pro-ana frames in those channels were also connective (OR=1.55;\n P<\/jats:italic>\n =.003).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n Pro-ana discourse on YouTube is fragmented into \u201crefracted publics.\u201d Meso-level individual channels using recovery narratives serve as critical bridges across polarized frames. Public health efforts should partner with mid-tier influencers to co-create emotionally resonant recovery content that disrupts echo chambers and fosters cross-frame dialogue.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/77168","type":"journal-article","created":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T16:50:07Z","timestamp":1760633407000},"page":"e77168-e77168","source":"Crossref","is-referenced-by-count":2,"title":["Framing Pro-Anorexia Discourse on YouTube in South Korea: Social Network and Exponential Random Graph Model Analysis of Video Communities"],"prefix":"10.2196","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-1805-8488","authenticated-orcid":false,"given":"Daseul","family":"Oh","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2817-3969","authenticated-orcid":false,"given":"Shin Haeng","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2025,11,4]]},"reference":[{"issue":"1","key":"R1","doi-asserted-by":"publisher","DOI":"10.1177\/2056305120984458","article-title":"From \u201cnetworked publics\u201d to \u201crefracted publics\u201d: a companion framework for researching \u201cbelow the radar\u201d studies","volume":"7","author":"Abidin","journal-title":"Social Media + Society"},{"issue":"11-12","key":"R2","doi-asserted-by":"publisher","first-page":"2589","DOI":"10.1177\/1461444819854731","article-title":"Managing visibility on YouTube through algorithmic gossip","volume":"21","author":"Bishop","journal-title":"New Media & Society"},{"issue":"1","key":"R3","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1177\/1354856517736982","article-title":"From ranking algorithms to \u201cranking cultures\u201d: investigating the modulation of visibility in YouTube search results","volume":"24","author":"Rieder","journal-title":"Convergence"},{"key":"R4","unstructured":"Burgess J Green J . 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