Keyword–platform relationships in social media research: insights into computer science conference proceedings

Kazuhiro Yamauchi, Takaharu Matsuda, Marie Katsurai

Abstract: PurposeThis study examined the evolution of social media platforms as data sources for researchers in computer science research. This study also analyzed the unique research themes associated with different social media platforms.Design/methodology/approachWe conducted a bibliometric analysis of more than 4,000 papers from three major computer science conferences related to social media research, from 2013 to 2023. We manually extracted the names of the platforms used as data sources from research titles and abstracts. Subsequently, keyword co-occurrence networks and heat maps were created to illustrate the relationships between platforms and research topics.FindingsSocial media has grown in importance as a data source, and Twitter (now “X”) represents a central platform in the field of computer science. Each platform exhibited distinct research themes: Twitter was prominent in political and disaster-related research, Reddit in online community studies, and platforms such as YouTube and Instagram in video- and image-based research. Three main research areas emerged across platforms: machine learning, network science, and social science.Originality/valueThis study provides an overview of the social media research trends in computer science, offering insights into platform-specific research themes and the evolving importance of social media data in academic research. These findings highlight the potential impact of the recent changes in data access policies on future research.

External IDs:doi:10.1108/ajim-11-2024-0890