Public Insights on COVID19 Vaccination using Exploratory and Sentiment Analysis on tweets [journal]

Journal

Journal of Software Engineering and Simulation - September 2021

Authors

Aryan Srivastava, Debarati Das (Ph.D. student)

Abstract

COVID-19, a major topic of discussion in every field, has shaken up the entire world. It is at times like these that social media blows up and the activity on these platforms drastically increases. In the past one year, there have been a lot of tweets related to Corona Virus and its Vaccines. This paper focuses towards exploring innumerable tweets regarding covid vaccines to summarize the public's opinion and discover key inferences from this data-set. This data-set pertains to the tweets related to the following vaccines:

  • Pfizer/BioNTech
  • Sinopharm
  • Sinovac
  • Moderna
  • Oxford/AstraZeneca
  • Covaxin
  • Sputnik V

Through the course of this paper, you will find word clouds, time series plots, histograms etc to show important features of this data-set like retweet counts with time, average text length, countries from where tweets have come, and many more. I have also carried out basic sentiment and emotional analysis on the tweets (using lexical features) to display the public’s feedback about COVID 19 Vaccines. The objective of this paper is to eliminate the problem of twitter users, browsing through thousands of tweets to summarize the public's opinion about the covid vaccines to make their personal decisions about related situations.

Link to full paper

Public Insights on COVID19 Vaccination using Exploratory and Sentiment Analysis on tweets

Keywords

COVID-19, data mining

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