Investigation of the Gender-Specific Discourse about Online Learning during COVID-19 on Twitter Using Sentiment Analysis, Subjectivity Analysis, and Toxicity Analysis
This paper presents several novel findings from a comprehensive analysis of about 50,000 Tweets about online learning during COVID-19, posted on Twitter between 9 November 2021 and 13 July 2022. First, the results of sentiment analysis from VADER, Afinn, and TextBlob show that a higher percentage of...
Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-10-01
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Series: | Computers |
Subjects: | |
Online Access: | https://www.mdpi.com/2073-431X/12/11/221 |