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Exploring Coronavirus Disease 2019 Vaccine Hesitancy on Twitter Using Sentiment Analysis and Natural Language Processing Algorithms.

Anasse BariMatthias HeymannRyan J CohenRobin ZhaoLevente SzaboShailesh Apas VasandaniAashish KhubchandaniMadeline DiLorenzoMegan Coffee
Published in: Clinical infectious diseases : an official publication of the Infectious Diseases Society of America (2022)
Social media has influenced the COVID-19 response through valuable information and misinformation and distrust. This tool was used to collect and analyze tweets at scale in real time to study sentiment and key terms of interest. Separate tweet analysis showed that vaccination rates tracked regionally with Twitter vaccine sentiment and might forecast changes in vaccine uptake and/or guide targeted social media and vaccination strategies. Further work is needed to analyze the interplay between specific populations, vaccine sentiment, and vaccination rates.
Keyphrases
  • social media
  • coronavirus disease
  • health information
  • sars cov
  • cancer therapy
  • deep learning
  • respiratory syndrome coronavirus