{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T04:30:11Z","timestamp":1772253011635,"version":"3.50.1"},"reference-count":69,"publisher":"American Association for the Advancement of Science (AAAS)","content-domain":{"domain":["spj.science.org"],"crossmark-restriction":true},"short-container-title":["Health Data Sci"],"published-print":{"date-parts":[[2024,1]]},"abstract":"<jats:p>\n                    <jats:bold>Background:<\/jats:bold>\n                    The COVID-19 pandemic has caused a disproportionate impact on the sexual and gender-diverse (SGD) community. Compared with non-SGD populations, their social relations and health status are more vulnerable, whereas public health data regarding SGD are scarce.\n                    <jats:bold>Methods:<\/jats:bold>\n                    To analyze the concerns and health status of SGD individuals, this cohort study leveraged 471,371,477 tweets from 251,455 SGD and 22,644,411 non-SGD users, spanning from 2020 February 1 to 2022 April 30. The outcome measures comprised the distribution and dynamics of COVID-related topics, attitudes toward vaccines, and the prevalence of symptoms.\n                    <jats:bold>Results:<\/jats:bold>\n                    Topic analysis revealed that SGD users engaged more frequently in discussions related to \u201cfriends and family\u201d (20.5% vs. 13.1%,\n                    <jats:italic>P<\/jats:italic>\n                    &lt; 0.001) and \u201cwear masks\u201d (10.1% vs. 8.3%,\n                    <jats:italic>P<\/jats:italic>\n                    &lt; 0.001) compared to non-SGD users. Additionally, SGD users exhibited a marked higher proportion of positive sentiment in tweets about vaccines, including Moderna, Pfizer, AstraZeneca, and Johnson &amp; Johnson. Among 102,464 users who self-reported COVID-19 diagnoses, SGD users disclosed significantly higher frequencies of mentioning 61 out of 69 COVID-related symptoms than non-SGD users, encompassing both physical and mental health challenges.\n                    <jats:bold>Conclusion:<\/jats:bold>\n                    The results provide insights into an understanding of the unique needs and experiences of the SGD community during the pandemic, emphasizing the value of social media data in epidemiological and public health research.\n                  <\/jats:p>","DOI":"10.34133\/hds.0127","type":"journal-article","created":{"date-parts":[[2024,7,25]],"date-time":"2024-07-25T16:53:09Z","timestamp":1721926389000},"update-policy":"https:\/\/doi.org\/10.34133\/aaas_crossmark_01","source":"Crossref","is-referenced-by-count":2,"title":["Sexual and Gender-Diverse Individuals Face More Health Challenges during COVID-19: A Large-Scale Social Media Analysis with Natural Language Processing"],"prefix":"10.34133","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-0095-6236","authenticated-orcid":true,"given":"Zhiyun","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Big Data in Health Science School of Public Health, \rZhejiang University School of Medicine, Hangzhou, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yining","family":"Hua","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, \rHarvard T.H. Chan School of Public Health, Boston, MA, USA."},{"name":"Department of Biomedical Informatics, \rHarvard Medical School, Boston, MA, USA."},{"name":"Division of General Internal Medicine and Primary Care, Department of Medicine, \rBrigham and Women\u2019s Hospital, Boston, MA, USA."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peilin","family":"Zhou","sequence":"additional","affiliation":[{"name":"Thrust of Data Science and Analytics, \rThe Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shixu","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Big Data in Health Science School of Public Health, \rZhejiang University School of Medicine, Hangzhou, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minghui","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Big Data in Health Science School of Public Health, \rZhejiang University School of Medicine, Hangzhou, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yujie","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Big Data in Health Science School of Public Health, \rZhejiang University School of Medicine, Hangzhou, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Zhou","sequence":"additional","affiliation":[{"name":"Division of General Internal Medicine and Primary Care, Department of Medicine, \rBrigham and Women\u2019s Hospital, Boston, MA, USA."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanhui","family":"Liao","sequence":"additional","affiliation":[{"name":"Department of Psychiatry, Sir Run Run Shaw Hospital, \rZhejiang University School of Medicine, Hangzhou, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5696-363X","authenticated-orcid":true,"given":"Jie","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Big Data in Health Science School of Public Health, \rZhejiang University School of Medicine, Hangzhou, China."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"221","published-online":{"date-parts":[[2024,9,6]]},"reference":[{"issue":"9","key":"e_1_3_4_2_2","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1136\/jech-2020-214720","article-title":"COVID-19: Exposing and amplifying inequalities","volume":"74","author":"Marmot M","year":"2020","unstructured":"Marmot M, Allen J. 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