Computational communication research (CCR): An early and active adopter of computational social science (CSS)

Computational communication research (CCR) has emerged as an early and active subfield within computational social science, offering novel methodological approaches to address classical and emerging questions in communication research. This paper reviews the evolution and methodological developments in CCR in both the international research community and Chinese mainland, emphasizing the role of computational methods such as user analytics, content mining, and computational experiments. We map the alignment between traditional quantitative methods and computational ones, demonstrating how CCR methods have complemented and enhanced existing research paradigms. Through empirical applications, we illustrate the utility of CCR in understanding user behavior, content dynamics, and communication effects. We conclude with a discussion on the challenges of using computational methods in the Chinese context and the future directions for CCR.

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Publication Details

Journal
Chinese Journal of Sociology
Published
2025-01-01
DOI
https://doi.org/10.1177/2057150x251317548
Primary Topic
Social Media and Politics
Type
article
Field-Weighted Citation Impact
0.00
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article

Computational communication research (CCR): An early and active adopter of computational social science (CSS)

Hai Liang, Tai‐Quan Peng, Jonathan J. H. Zhu
Chinese Journal of Sociology
Social Media and Politics
article

Computational communication research (CCR): An early and active adopter of computational social science (CSS)

Hai Liang, Tai‐Quan Peng, Jonathan J. H. Zhu
article en

Abstract

Computational communication research (CCR) has emerged as an early and active subfield within computational social science, offering novel methodological approaches to address classical and emerging questions in communication research. This paper reviews the evolution and methodological developments in CCR in both the international research community and Chinese mainland, emphasizing the role of computational methods such as user analytics, content mining, and computational experiments. We map the alignment between traditional quantitative methods and computational ones, demonstrating how CCR methods have complemented and enhanced existing research paradigms. Through empirical applications, we illustrate the utility of CCR in understanding user behavior, content dynamics, and communication effects. We conclude with a discussion on the challenges of using computational methods in the Chinese context and the future directions for CCR.

Chinese Journal of SociologyVol. 11(1)
City University of Hong Kong (HK), Chinese University of Hong Kong (HK), Michigan State University (US)
Openalex Percentile: Top 94%
Social Media and Politics
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