Emotion Analysis on COVID-related Twitter Tweets

Maliha Haider, Daehan Kwak

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

As the COVID-19 pandemic surged in 2020 and 2021, with an increasing number of people getting sick every day, it is important to analyze how the public reacted to the crisis. The purpose of this study is to gain an understanding of how peoples' emotions changed over the course of the pandemic. Understanding how people responded to COVID-19 will help society have a clearer view of peoples' emotions and how they handled the pandemic. Social media is a common way that the public communicates their thoughts and opinions, thus, this study focuses on detecting emotions on Twitter tweets that were posted during the pandemic. 364,254 tweets are collected, processed, and associated with eight basic emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust) along with two sentiments (negative and positive).

Original languageEnglish
Title of host publicationProceedings - 2023 International Conference on Computational Science and Computational Intelligence, CSCI 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages747-752
Number of pages6
ISBN (Electronic)9798350361513
DOIs
StatePublished - 2023
Event2023 International Conference on Computational Science and Computational Intelligence, CSCI 2023 - Las Vegas, United States
Duration: 13 Dec 202315 Dec 2023

Publication series

NameProceedings - 2023 International Conference on Computational Science and Computational Intelligence, CSCI 2023

Conference

Conference2023 International Conference on Computational Science and Computational Intelligence, CSCI 2023
Country/TerritoryUnited States
CityLas Vegas
Period13/12/2315/12/23

Keywords

  • COVID-19
  • Data Visualization
  • Emotion
  • Natural Language Processing
  • NRC Lexicon
  • Twitter

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