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It can also build theoretical understanding of how social life and citizenship incorporate social media usage. This study tracks the evolution of public sentiment in Wuhan, China, during the first 12\u2009weeks after the identification of COVID-19 on the Chinese microblogging platform Sina Weibo. Data consist of 133,079 original Sina Weibo posts dealing with the novel coronavirus. The relative prevalence of eight different emotion groups is traced longitudinally using the ROST Content Mining System and the Emotion Vocabulary of Dalian University of Technology. The study finds a progression from confusion\/fear, to disappointment\/frustration, to depression\/anxiety, then finally to happiness\/gratitude. It argues that this progression indexes the changing affective energies of digital medical citizenship, which in turn indicates the context for intervention in future crises. <\/jats:p>","DOI":"10.1177\/14614448211058850","type":"journal-article","created":{"date-parts":[[2021,11,27]],"date-time":"2021-11-27T09:11:30Z","timestamp":1638004290000},"page":"346-367","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":20,"title":["Shifting moods on Sina Weibo: The first 12\u2009weeks of COVID-19 in Wuhan"],"prefix":"10.1177","volume":"26","author":[{"given":"Peng","family":"Zheng","sequence":"first","affiliation":[{"name":"Zhengzhou University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9303-0027","authenticated-orcid":false,"given":"Paul C","family":"Adams","sequence":"additional","affiliation":[{"name":"The University of Texas at Austin, USA"}]},{"given":"Jiejie","family":"Wang","sequence":"additional","affiliation":[{"name":"Henan University of Economics and Law, China"}]}],"member":"179","published-online":{"date-parts":[[2021,11,27]]},"reference":[{"key":"bibr1-14614448211058850","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0186836"},{"key":"bibr2-14614448211058850","unstructured":"BBC News (2016) Sina Weibo ends 140-character limit ahead of Twitter (Tech Section). 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