Sentiments towards Emergency Remote Teaching on Twitter: A Longitudinal Comparative Sentiment Analysis

Year 2023, , 1 - 21, 30.04.2023

Secil Caskurlu , Serkan Ayvaz Kadir Kozan

https://doi.org/10.54535/rep.1206924

Cited By: 1

Abstract

This longitudinal and comparative study investigated people’s sentiments toward emergency remote teaching in tweets posted in two different languages from January 10 to August 16 2021 when mass vaccinations started and continued. The results indicated that English tweets (a) included more positive sentiments towards emergency remote teaching; (b) were more supportive and motivating; and (c) focused on topics related to education, online education, and English as a second or foreign language. However, Turkish tweets (a) included more similar amounts of neutral and positive sentiments; (b) involved politics and government-related content; and (c) touched on topics related to preschool education, ministry of national education and the e-school system used during the pandemic. Lastly, compared to positive and neutral sentiments, there were fewer negative sentiments in tweets in both languages suggesting that people got used to emergency remote teaching over time. In other words, despite any ongoing issues, people’s reactions to emergency remote teaching on Twitter improved and became either more neutral or positive in a year or so, which implies that increasing optimism due to vaccinations during sudden health crises may calibrate people’s sentiments towards compulsory solutions such as emergency remote teaching.

Keywords

Comparative sentiment analysis, Emergency online education, Emergency remote teaching, Text mining, Topic modeling, Twitter

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