{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T06:00:09Z","timestamp":1785218409880,"version":"3.55.0"},"reference-count":50,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T00:00:00Z","timestamp":1785196800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Psychol."],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study analyzes differences in depression-related expressions between healthcare professionals and non-healthcare individuals on Chinese social media.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Sentiment plays a critical role in depression management, influencing condition assessment, social support, and treatment adherence. However, traditional research methods are limited by self-report bias, small samples, and constrained expression. Social media offers a unique platform to capture authentic emotions at scale.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A total of 120,895 comments were retrieved from Zhihu, Weibo, and Xiaohongshu. Data underwent cleaning, relevance verification, and anonymization. Users were classified into healthcare professionals and non-healthcare individuals through profile verification and manual annotation. Sentiment analysis applied the Dalian University of Technology Sentiment Lexicon, adapted to Chinese contexts and grounded in Ekman's emotional framework (anger, disgust, fear, sadness, surprise, positive emotion). Polarity and intensity (\u22121 to 1) were quantified. Content analysis employed a K-Means clustering algorithm to identify thematic patterns. Content analysis was conducted using computational text analysis methods, including sentiment analysis and K-means clustering, to identify emotional and thematic patterns in depression-related social media discourse.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Non-healthcare individuals expressed a wider emotional spectrum (anger, disgust, fear, sadness, surprise, and positive emotions), while healthcare professionals primarily expressed anger, fear, and positive emotions. Non-healthcare discourse focused on illness experiences, stigma, and treatment conflict, whereas healthcare professionals emphasized occupational stress, emotional labor, and professional fulfillment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The results highlight divergent emotional orientations: patients and the public center on illness experiences, while professionals emphasize identity and occupational strain. These differences underscore the need for tailored communication strategies, empathy training, and institutional psychological support for healthcare providers.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpsyg.2026.1858436","type":"journal-article","created":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T05:35:00Z","timestamp":1785216900000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Comparative sentiment and thematic analysis of depression-related discourse between healthcare professionals and non-healthcare individuals on Chinese social media: a computational text analysis study"],"prefix":"10.3389","volume":"17","author":[{"given":"Qi","family":"Zhou","sequence":"first","affiliation":[{"name":"Hangzhou Linping District Integrated Traditional Chinese and Western Medicine Hospital","place":["Hangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuxi","family":"Chen","sequence":"additional","affiliation":[{"name":"Hangzhou Linping District Integrated Traditional Chinese and Western Medicine Hospital","place":["Hangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Li","sequence":"additional","affiliation":[{"name":"Medicine department, Huzhou University, Hangzhou","place":["Zhejiang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lili","family":"Yang","sequence":"additional","affiliation":[{"name":"Nursing education department, Sir Run Run Shaw Hospital of Zhejiang University","place":["Hangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qinrou","family":"Yu","sequence":"additional","affiliation":[{"name":"Nursing department, Hangzhou Normal University","place":["Hangzhou, Zhejiang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lihui","family":"Yan","sequence":"additional","affiliation":[{"name":"Hangzhou Linping District Integrated Traditional Chinese and Western Medicine Hospital","place":["Hangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Danhong","family":"Qian","sequence":"additional","affiliation":[{"name":"Hangzhou Linping District Integrated Traditional Chinese and Western Medicine Hospital","place":["Hangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,7,28]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"587","DOI":"10.1097\/NMD.0000000000001813","article-title":"The mediating role of emotion regulation difficulties in the correlation between mindfulness and psychological resilience in patients diagnosed with depression","volume":"212","author":"Arpaci","year":"2024","journal-title":"J. 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