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Cited by 313

The DOI matches its Crossref record; 88 of the 88 references it cites were found in a registry or an index.

Social Networks and Political Participation

Campbell, David E.·2013·Annual Review of Political Science
DOI 10.1146/annurev-polisci-033011-201728
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Abstract

In recent years, the study of political participation has benefited from growing attention to the study of social networks. Historically, most explanations for political participation have focused on characteristics of individuals. Although these individual-level correlates do a “pretty good” job of predicting who participates, incorporating social networks deepens our understanding of the factors that lead people to express voice in the democratic process. Even though the participation literature has long been split between scholars who favor a focus on individuals and others who emphasize social networks, the two approaches need not be in tension. Instead, they complement one another. The individualistic factors known to correlate with participation—including education, religious attendance, political knowledge, political conviction, and civic duty—all have a social dimension.

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Metadata

Authors
Campbell, D. E.
Venue
Annual Review of Political Science
Publisher
Annual Reviews
Published
2013-05-11
Volume
16
Issue
1
Pages
33-48
ISSN
  • 1094-2939 (ISSN-L)
  • 1545-1577
DOI
10.1146/annurev-polisci-033011-201728
OpenAlex
W2098073218
Cited by
313
References
88
FWCI
36.17
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Social Networks and Political Participation. https://app.cochat.ai/papers/10.1146/annurev-polisci-033011-201728
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Campbell, D. E. (2013). Social Networks and Political Participation. Annual Review of Political Science. https://doi.org/10.1146/annurev-polisci-033011-201728

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.