{"title":"COVID-19大流行早期推特用户的担忧——未来公共卫生传播的教训:一项基于推特的混合方法研究","authors":"Harshal B Sonekar, Kumaravel Ilangovan, Suganya Barani, Sendhilkumar Muthappan, Gowtham Sockalingam, Malathi Mathiyazhakan, Manickam Ponnaiah","doi":"10.4103/jfmpc.jfmpc_1556_24","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>During COVID-19, the government and public health sectors used Twitter for disseminating information on health, awareness and preventing measures. However, resources on infodemics of the public responses and their personal expressions in the evolutionary stages of the pandemic at a global level is limited. We explored the topics discussed by the Tweeples related to COVID-19.</p><p><strong>Methods: </strong>We retrieved English language tweets from 25 December 2019 to 26 March 2020 containing the keywords 'Corona' or 'nCoV' or 'Covid' or 'SARS' or 'virus' using the Twitter's application programme interface (API) in Python 3.7 with predefined codes. Trend graphs were generated using the counts and proportions of keyword tweets and the number of retweets of the keyword tweets. We performed thematic analysis with selected 1400 (100 from every Thursday) tweets for emerging topics and critically appraised the themes.</p><p><strong>Results: </strong>We identified that Tweeples' were discussing the coronavirus pandemic a week before official notification. 'Corona' (60%) and 'COVID' (26%) were the most popular terms. We constructed six common themes including awareness, emotions, beliefs, politics, economy and controversies. Key topics of the tweets during the early stages were the economic impact and scientific information of COVID-19, stigma and discrimination, general awareness, personal reactions, social support and conspirational theories.</p><p><strong>Conclusion: </strong>During the evolutionary phase of the COVID-19 pandemic, a rapid knowledge transition was observed. Twitter as a vibrant social media can be used for early identification of disease outbreak, perception and communication of the community, thus complementing the existing disease-surveillance and management systems.</p>","PeriodicalId":15856,"journal":{"name":"Journal of Family Medicine and Primary Care","volume":"14 8","pages":"3252-3258"},"PeriodicalIF":1.0000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12488146/pdf/","citationCount":"0","resultStr":"{\"title\":\"Tweeples' concerns during the early phase of COVID-19 Pandemic - Lessons for the future public health communications: A Twitter-based mixed methods study.\",\"authors\":\"Harshal B Sonekar, Kumaravel Ilangovan, Suganya Barani, Sendhilkumar Muthappan, Gowtham Sockalingam, Malathi Mathiyazhakan, Manickam Ponnaiah\",\"doi\":\"10.4103/jfmpc.jfmpc_1556_24\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>During COVID-19, the government and public health sectors used Twitter for disseminating information on health, awareness and preventing measures. However, resources on infodemics of the public responses and their personal expressions in the evolutionary stages of the pandemic at a global level is limited. We explored the topics discussed by the Tweeples related to COVID-19.</p><p><strong>Methods: </strong>We retrieved English language tweets from 25 December 2019 to 26 March 2020 containing the keywords 'Corona' or 'nCoV' or 'Covid' or 'SARS' or 'virus' using the Twitter's application programme interface (API) in Python 3.7 with predefined codes. Trend graphs were generated using the counts and proportions of keyword tweets and the number of retweets of the keyword tweets. We performed thematic analysis with selected 1400 (100 from every Thursday) tweets for emerging topics and critically appraised the themes.</p><p><strong>Results: </strong>We identified that Tweeples' were discussing the coronavirus pandemic a week before official notification. 'Corona' (60%) and 'COVID' (26%) were the most popular terms. We constructed six common themes including awareness, emotions, beliefs, politics, economy and controversies. Key topics of the tweets during the early stages were the economic impact and scientific information of COVID-19, stigma and discrimination, general awareness, personal reactions, social support and conspirational theories.</p><p><strong>Conclusion: </strong>During the evolutionary phase of the COVID-19 pandemic, a rapid knowledge transition was observed. Twitter as a vibrant social media can be used for early identification of disease outbreak, perception and communication of the community, thus complementing the existing disease-surveillance and management systems.</p>\",\"PeriodicalId\":15856,\"journal\":{\"name\":\"Journal of Family Medicine and Primary Care\",\"volume\":\"14 8\",\"pages\":\"3252-3258\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2025-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12488146/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Family Medicine and Primary Care\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4103/jfmpc.jfmpc_1556_24\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/9/24 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q4\",\"JCRName\":\"PRIMARY HEALTH CARE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Family Medicine and Primary Care","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4103/jfmpc.jfmpc_1556_24","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/9/24 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"PRIMARY HEALTH CARE","Score":null,"Total":0}
Tweeples' concerns during the early phase of COVID-19 Pandemic - Lessons for the future public health communications: A Twitter-based mixed methods study.
Background: During COVID-19, the government and public health sectors used Twitter for disseminating information on health, awareness and preventing measures. However, resources on infodemics of the public responses and their personal expressions in the evolutionary stages of the pandemic at a global level is limited. We explored the topics discussed by the Tweeples related to COVID-19.
Methods: We retrieved English language tweets from 25 December 2019 to 26 March 2020 containing the keywords 'Corona' or 'nCoV' or 'Covid' or 'SARS' or 'virus' using the Twitter's application programme interface (API) in Python 3.7 with predefined codes. Trend graphs were generated using the counts and proportions of keyword tweets and the number of retweets of the keyword tweets. We performed thematic analysis with selected 1400 (100 from every Thursday) tweets for emerging topics and critically appraised the themes.
Results: We identified that Tweeples' were discussing the coronavirus pandemic a week before official notification. 'Corona' (60%) and 'COVID' (26%) were the most popular terms. We constructed six common themes including awareness, emotions, beliefs, politics, economy and controversies. Key topics of the tweets during the early stages were the economic impact and scientific information of COVID-19, stigma and discrimination, general awareness, personal reactions, social support and conspirational theories.
Conclusion: During the evolutionary phase of the COVID-19 pandemic, a rapid knowledge transition was observed. Twitter as a vibrant social media can be used for early identification of disease outbreak, perception and communication of the community, thus complementing the existing disease-surveillance and management systems.