학술논문

COVID-19 Sentiment Analysis Based on Tweets
Document Type
Periodical
Source
IEEE Intelligent Systems IEEE Intell. Syst. Intelligent Systems, IEEE. 38(3):51-55 Jun, 2023
Subject
Computing and Processing
Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
COVID-19
Sentiment analysis
Pandemics
Social networking (online)
Mood
Blogs
Time measurement
Language
ISSN
1541-1672
1941-1294
Abstract
In this work, based on sentiment analysis of tweets, we investigate how individuals in Italy perceived the COVID-19 outbreak and its implications in real life. We unveil the most discussed narratives on Twitter and measure how users’ interests, sentiments, and emotions have evolved over time and across the several aspects of the pandemic. Our analysis shows that while the overall sentiment is negative, Italians have shown upbeat responses to the pandemic, especially in regards to the vaccination campaign. The emotion analysis reveals that while fear progressively decreased after the first wave of the pandemic, the overall anger has remained constant but gradually turned into various narratives.