Computational social science: Obstacles and opportunities
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Data sharing, research ethics, and incentives must improve
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The emergence of Computational Social Science (CSS) marks a transformative shift in the study of social phenomena, triggered by advancements in computational technology and large-scale collection of digital behavioral trace data.
“The emergence of Computational Social Science (CSS) marks a transformative shift in the study of social phenomena, triggered by advancements in computational technology and large-scale collection of (digital) behavioral trace data.”
From Computational Social Science of Social Cohesion and Polarization (2026) · cites this paper as Lazer et al. 2020
The new millennium has witnessed the Computational Social Science (CSS) revolution.
“The new millennium has witnessed the Computational Social Science (CSS) revolution (Lazer et al. 2009;Conte et al. 2012;Lazer et al. 2020).”
From Computational Social Science of Social Cohesion and Polarization (2026) · cites this paper as Lazer et al. 2020
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References 14 · Cited by 453
- Authors
- Lazer, D. M. J., Pentland, A., Watts, D. J., Aral, S., Athey, S., Contractor, N., Freelon, D., Gonzalez-Bailon, S., King, G., Margetts, H., Nelson, A., Salganik, M. J., Strohmaier, M., Vespignani, A., & Wagner, C.
- Affiliations
- Northeastern University (US)
- Massachusetts Institute of Technology (US)
- University of Pennsylvania (US)
- Stanford University (US)
- Northwestern University (US)
- University of North Carolina at Chapel Hill (US)
- University of Pennsylvania, Philadelphia, PA, USA.
- Harvard University (US)
- University of Oxford (GB)
- Social Science Research Council (US)
- Princeton University (US)
- GESIS - Leibniz Institute for the Social Sciences (DE)
- University of Koblenz and Landau (DE)
- ORCID
- Venue
- Science
- Published
- 2020-08-28
- Volume
- 369
- Issue
- 6507
- Pages
- 1060-1062
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W3081158114
- Cited by
- 453
- References
- 14
- Citations by year
- 2026: 85 · 2025: 59 · 2024: 70 · 2023: 90 · 2022: 76 · 2021: 65 · 2020: 8
- FWCI
- 59.26
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
- RWTH Publications (RWTH Aachen) (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
- Social Sciences › General Social Sciences › Computational and Text Analysis Methods
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Keywords
- computational social science, data sharing, research ethics, research incentives, barriers to research
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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