Sentiment Analysis and Topic Modeling Regarding Online Classes on the Reddit Platform: Educators versus Learners
Source abstract
Abstract
The world is witnessing an unpredictable COVID-19 pandemic that has impacted all levels of online education, shaping future trends. However, this shift was so sudden and drastic that unrevealed puzzles exist regarding the public’s authentic opinion towards online classes, even though three years have passed. Many experts and policymakers have conducted qualitative and quantitative research to explore effective pedagogies, the satisfaction of different stakeholders, and factors influential on learners’ performance. However, scant studies have examined personal opinions and concerns toward online classes hidden behind people’s anonymous posts on social media. This research investigates the sentiments, concerns, and their variance with time regarding online classes by learners and educators on Reddit, which is a dominant social network among them. Data were collected via the official API from identified relevant subreddits and keyword search results across Reddit. Sentiment analysis was applied to reveal their emotions and their changes. Topic modeling was conducted to discover the concerns hidden in the posts. The results revealed the concerns about online classes, such as severe cheating behaviors, and showed doubts about previous strategies to solve disadvantages in online classes. In addition, the results verified the habitual difference and motivations of social media usage between educators and learners.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Sentiment Analysis and Opinion Mining · Online Learning and Analytics · Misinformation and Its Impacts
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Faculty of Education, The University of Hong Kong, Hong Kong 999077, China
Graduate School of Business Sciences, Humanities and Social Sciences, University of Tsukuba, Tokyo 112-0012, Japan
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