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Revealing Public Opinion Towards COVID-19 Vaccines With Twitter Data in the United States: Spatiotemporal Perspective.
Hu, Tao; Wang, Siqin; Luo, Wei; Zhang, Mengxi; Huang, Xiao; Yan, Yingwei; Liu, Regina; Ly, Kelly; Kacker, Viraj; She, Bing; Li, Zhenlong.
Afiliação
  • Hu T; Department of Geography, Oklahoma State University, Stillwater, OK, United States.
  • Wang S; Center for Geographic Analysis, Harvard University, Cambridge, MA, United States.
  • Luo W; School of Earth and Environmental Sciences, University of Queensland, Brisbane, Australia.
  • Zhang M; Department of Geography, National University of Singapore, Singapore, Singapore.
  • Huang X; Department of Nutrition and Health Science, Ball State University, Muncie, IN, United States.
  • Yan Y; Department of Geosciences, University of Arkansas, Fayetteville, AR, United States.
  • Liu R; Department of Geography, National University of Singapore, Singapore, Singapore.
  • Ly K; Department of Biology, Mercer University, Macon, GA, United States.
  • Kacker V; Department of Computer Science, University of Massachusetts Lowell, Lowell, MA, United States.
  • She B; College of Computing, Georgia Institute of Technology, Atlanta, GA, United States.
  • Li Z; Institute for Social Research, University of Michigan, Ann Arbor, MI, United States.
J Med Internet Res ; 23(9): e30854, 2021 09 10.
Article em En | MEDLINE | ID: mdl-34346888
BACKGROUND: The COVID-19 pandemic has imposed a large, initially uncontrollable, public health crisis both in the United States and across the world, with experts looking to vaccines as the ultimate mechanism of defense. The development and deployment of COVID-19 vaccines have been rapidly advancing via global efforts. Hence, it is crucial for governments, public health officials, and policy makers to understand public attitudes and opinions towards vaccines, such that effective interventions and educational campaigns can be designed to promote vaccine acceptance. OBJECTIVE: The aim of this study was to investigate public opinion and perception on COVID-19 vaccines in the United States. We investigated the spatiotemporal trends of public sentiment and emotion towards COVID-19 vaccines and analyzed how such trends relate to popular topics found on Twitter. METHODS: We collected over 300,000 geotagged tweets in the United States from March 1, 2020 to February 28, 2021. We examined the spatiotemporal patterns of public sentiment and emotion over time at both national and state scales and identified 3 phases along the pandemic timeline with sharp changes in public sentiment and emotion. Using sentiment analysis, emotion analysis (with cloud mapping of keywords), and topic modeling, we further identified 11 key events and major topics as the potential drivers to such changes. RESULTS: An increasing trend in positive sentiment in conjunction with a decrease in negative sentiment were generally observed in most states, reflecting the rising confidence and anticipation of the public towards vaccines. The overall tendency of the 8 types of emotion implies that the public trusts and anticipates the vaccine. This is accompanied by a mixture of fear, sadness, and anger. Critical social or international events or announcements by political leaders and authorities may have potential impacts on public opinion towards vaccines. These factors help identify underlying themes and validate insights from the analysis. CONCLUSIONS: The analyses of near real-time social media big data benefit public health authorities by enabling them to monitor public attitudes and opinions towards vaccine-related information in a geo-aware manner, address the concerns of vaccine skeptics, and promote the confidence that individuals within a certain region or community have towards vaccines.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Mídias Sociais / COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Mídias Sociais / COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Ano de publicação: 2021 Tipo de documento: Article