Emotion Analysis on COVID-related Twitter Tweets

被引:1
作者
Haider, Maliha [1 ]
Kwak, Daehan [1 ]
机构
[1] Kean Univ, Dept Comp Sci & Technol, Union, NJ 07083 USA
来源
2023 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE, CSCI 2023 | 2023年
基金
美国国家科学基金会;
关键词
Emotion; COVID-19; Twitter; Data Visualization; NRC Lexicon; Natural Language Processing; SENTIMENT ANALYSIS;
D O I
10.1109/CSCI62032.2023.00127
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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).
引用
收藏
页码:747 / 752
页数:6
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