Sentiment Analysis in Communication Studies: A Bibliographic Study on Web of Science Indexed Articles

Abstract

This study aims to map the intellectual structure, chronological evolution, and social networks of sentiment analysis research within the field of communication. As digital text data grows, text-as-data methods have become central to communication studies; however, a comprehensive bibliometric evaluation of this domain remains limited. The research analyzes 298 articles indexed in the Web of Science (SSCI and ESCI) between 2011 and 2025 using the PRISMA protocol. A hybrid methodological approach was adopted, combining computational bibliometric analysis via the R-bibliometrix package with manual quantitative content analysis. The findings reveal that sentiment analysis related studies experienced a latency period between 2011 and 2015, followed by exponential growth, particularly after 2020. Thematically, the literature clusters around political communication, journalism, and crisis communication, with a heavy reliance on social media data. While the United States leads in total scientific production, European countries demonstrate higher centrality in international collaboration networks. A critical finding is the field’s platform dependency, as 32% of the studies exclusively rely on Twitter (X) data. The study concludes that while sentiment analysis has matured from an experimental technique to a core methodology in communication, it risks methodological stagnation due to data source limitations. Future research is suggested to focus on multimodal analysis and diverse digital platforms to overcome these constraints.