TY - GEN
T1 - Emotion Analysis on COVID-related Twitter Tweets
AU - Haider, Maliha
AU - Kwak, Daehan
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - 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).
AB - 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).
KW - COVID-19
KW - Data Visualization
KW - Emotion
KW - Natural Language Processing
KW - NRC Lexicon
KW - Twitter
UR - http://www.scopus.com/inward/record.url?scp=85199987036&partnerID=8YFLogxK
U2 - 10.1109/CSCI62032.2023.00127
DO - 10.1109/CSCI62032.2023.00127
M3 - Conference contribution
AN - SCOPUS:85199987036
T3 - Proceedings - 2023 International Conference on Computational Science and Computational Intelligence, CSCI 2023
SP - 747
EP - 752
BT - Proceedings - 2023 International Conference on Computational Science and Computational Intelligence, CSCI 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 International Conference on Computational Science and Computational Intelligence, CSCI 2023
Y2 - 13 December 2023 through 15 December 2023
ER -