Computational Social Science and Sociology
Open accessAbstract
The integration of social science with computer science and engineering fields has produced a new area of study: computational social science. This field applies computational methods to novel sources of digital data such as social media, administrative records, and historical archives to develop theories of human behavior. We review the evolution of this field within sociology via bibliometric analysis and in-depth analysis of the following subfields where this new work is appearing most rapidly: ( a) social network analysis and group formation; ( b) collective behavior and political sociology; ( c) the sociology of knowledge; ( d) cultural sociology, social psychology, and emotions; ( e) the production of culture; ( f) economic sociology and organizations; and ( g) demography and population studies. Our review reveals that sociologists are not only at the center of cutting-edge research that addresses longstanding questions about human behavior but also developing new lines of inquiry about digital spaces as well. We conclude by discussing challenging new obstacles in the field, calling for increased attention to sociological theory, and identifying new areas where computational social science might be further integrated into mainstream sociology.
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In quantitative sociology, CSS has had a major impact across the board, overtaking fields like social network analysis and group formation, collective behavior and political sociology, the sociology of knowledge, cultural sociology, social psychology, and emotions, the production of culture, economic sociology and organizations, and demography and population studies.
“In quantitative sociology, CSS has had a major impact across the board, overtaking fields like social network analysis and group formation, collective behavior and political sociology, the sociology of knowledge, cultural sociology, social psychology, and emotions, the production of culture, economic sociology and organizations, and demography and population studies (Edelmann et al. 2020).”
From Computational Social Science of Social Cohesion and Polarization (2026) · cites this paper as Edelmann et al. 2020
The Introduction says CSS is spreading rapidly and identifies the seven listed areas as subfields with at least five qualifying studies. It does not say CSS is 'overtaking' those fields or has had an impact 'across the board'; the Conclusion says it has not yet been broadly integrated into many other large sociology subfields. (LLM, conf=0.88)
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Cites
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Can Generative AI improve social science?
Bail, C. A. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2314021121 · Cited by 369 · see citing works
Self-citationCan Generative AI Improve Social Science?
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Self-citationComputational Social Science of Social Cohesion and Polarization
Keijzer, M. A., Lorenz, J., & Bojanowski, M. (2026) · Computational Social Sciences · doi:10.1007/978-3-032-01373-6_1
- Authors
- Edelmann, A., Wolff, T., Montagne, D., & Bail, C. A.
- Affiliations
- University of Bern (CH)
- Duke University (US)
- Venue
- Annual Review of Sociology
- Publisher
- Annual Reviews
- Published
- 2020-07-30
- Volume
- 46
- Issue
- 1
- Pages
- 61-81
- ISSN
- 0360-0572 (ISSN-L)
- 1545-2115
- PMC
- PMC8612450
- OpenAlex
- W3022499311
- Cited by
- 305
- References
- 7
- Citations by year
- 2026: 46 · 2025: 48 · 2024: 52 · 2023: 64 · 2022: 51 · 2021: 36 · 2020: 8
- FWCI
- 6.70
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- public-domain
- Locations
- Annual Review of Sociology (publishedVersion, public-domain)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (P2CHD065563)
- Topics
- Social Sciences › General Social Sciences › Computational and Text Analysis Methods
- Social Sciences › Arts and Humanities › Literature and Literary Theory › Digital Humanities and Scholarship
- Physical Sciences › Computer Science › Artificial Intelligence › Multi-Agent Systems and Negotiation
- Keywords
- computational social science, digital data, social network analysis, group formation, collective behavior, political sociology, sociology of knowledge, sociology of culture, social psychology, emotions, cultural production, economic sociology, organizations, demography, population studies, human behavior, digital space, sociological theory
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