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 media; Consumer health information; Schema theory; Unsupervised machine learning; Social network analysis; SOCIAL MEDIA; FEAR APPEALS; ONLINE; COMMUNICATION; AFFORDANCES; SENTIMENT; FEATURES; ANGER; NEED
제목
Examining thematic and emotional differences across Twitter, Reddit, and YouTube: The case of COVID-19 vaccine side effects
저자
Kwon, Soyeon; Park, Albert
DOI
10.1016/j.chb.2023.107734
발행일
2023-07
유형
Article
저널명
Computers in Human Behavior
권
144
페이지
1 ~ 15