Sentiment Analysis of Tweets on the COVID-19 Pandemic Using Machine Learning Techniques

  • R. Jothikumar
  • , Vijayr Anand
  • , P. Visu
  • , R. Kumar
  • , S. Susi
  • , K. R. Kumar

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Sentiment evaluation alludes to separate the sentiments from the characteristic language and to perceive the mentality about the exact theme. Novel corona infection, a harmful malady ailment, is spreading out of the blue through the quarter, which thought processes respiratory tract diseases that can change from gentle to extraordinary levels. Because of its quick nature of spreading and no conceived cure, it ushered in a vibe of stress and pressure. In this chapter, a framework perusing principally based procedure is utilized to discover the musings of the tweets related to COVID and its effect lockdown. The chapter examines the tweets identified with the hash tags of crown infection and lockdown. The tweets were marked fabulous, negative, or fair, and a posting of classifiers has been utilized to investigate the precision and execution. The classifiers utilized have been under the four models which incorporate decision tree, regression, helpful asset vector framework, and naïve Bayes forms.

Original languageEnglish
Title of host publicationResearch Anthology on Implementing Sentiment Analysis across Multiple Disciplines
Subtitle of host publicationVolume I-IV
PublisherIGI Global
Pages1750-1760
Number of pages11
Volume1-4
ISBN (Electronic)9781668463048
ISBN (Print)9781668463031
DOIs
Publication statusPublished - 1 Jan 2022
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

ASJC Scopus subject areas

  • General Computer Science

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