Examining thematic and emotional differences across Twitter, Reddit, and YouTube: The case of COVID-19 vaccine side effects

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초록

Social media discourse has become a key data source for understanding the public's perception of, and senti-ments during a public health crisis. However, given the different niches which platforms occupy in terms of information exchange, reliance on a single platform would provide an incomplete picture of public opinions. Based on the schema theory, this study suggests a 'social media platform schema' to indicate users' different expectations based on previous usages of platform and argues that a platform's distinct characteristics foster distinct platform schema and, in turn, distinct nature of information. We analyzed COVID-19 vaccine side effect -related discussions from Twitter, Reddit, and YouTube, each of which represents a different type of the platform, and found thematic and emotional differences across platforms. Thematic analysis using k-means clustering algorithm identified seven clusters in each platform. To computationally group and contrast thematic clusters across platforms, we employed modularity analysis using the Louvain algorithm to determine a semantic network structure based on themes. We also observed differences in emotional contexts across platforms. Theoretical and public health implications are then discussed.

키워드

Social mediaConsumer health informationSchema theoryUnsupervised machine learningSocial network analysisSOCIAL MEDIAFEAR APPEALSONLINECOMMUNICATIONAFFORDANCESSENTIMENTFEATURESANGERNEED
제목
Examining thematic and emotional differences across Twitter, Reddit, and YouTube: The case of COVID-19 vaccine side effects
저자
Kwon, SoyeonPark, Albert
DOI
10.1016/j.chb.2023.107734
발행일
2023-07
유형
Article
저널명
Computers in Human Behavior
144
페이지
1 ~ 15