Analysis of Covid-19 News Using Text Mining Techniques


Cagatay E., Sunnetci B. Y., Orbay S., Kaya T.

4th International Conference on Intelligent and Fuzzy Systems (INFUS), Bornova, Turkey, 19 - 21 July 2022, vol.505, pp.438-445 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 505
  • Doi Number: 10.1007/978-3-031-09176-6_50
  • City: Bornova
  • Country: Turkey
  • Page Numbers: pp.438-445
  • Keywords: Clustering, Coronavirus, COVID-19, Sentiment analysis, Text mining, Vaccination
  • Istanbul Technical University Affiliated: Yes

Abstract

COVID-19, which has taken the whole world under its influence, has been a remarkable period to investigate the emotions and behaviors of people in extraordinary situations. The findings addressed during this defining moment to the fluctuation of the number of cases and certain turning points. It is a matter of debate how much these important moments are affected by the attitudes of the authorities directing the public. The aim of this study is to determine in which periods and what expressions the news in the newspapers is used by using text mining techniques such as word clouds, clustering and sentiment analysis. In order to do this, COVID-19 news published in the last two years from three respected newspapers were used. Results reveal that, there are significant changes in the main themes of the COVID-19 related news with the release of the vaccine. Moreover, when all periods are inspected, it has been observed that different topics like herd immunity, vaccination, variants and human rights have come to the forefront in various print media sources.