Characterizing Public Sentiments and Drug Interactions in the COVID-19 Pandemic Using Social Media: Natural Language Processing and Network Analysis.

Journal: Journal of medical Internet research
PMID: 40053730

Abstract

BACKGROUND: While the COVID-19 pandemic has induced massive discussion of available medications on social media, traditional studies focused only on limited aspects, such as public opinions, and endured reporting biases, inefficiency, and long collection times.

Authors

  • Wanxin Li
    School of Public Health, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Yining Hua
    Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
  • Peilin Zhou
    Thrust of Data Science and Analytics, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, Guangdong, 511458, China.
  • Li Zhou
    School of Education, China West Normal University, Nanchong, Sichuan, China.
  • Xin Xu
    State Key Laboratory of Oral Diseases, Sichuan University, Chengdu, China.
  • Jie Yang
    Key Laboratory of Development and Maternal and Child Diseases of Sichuan Province, Department of Pediatrics, Sichuan University, Chengdu, China.

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