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Testing Social Science Network Theories with Online Network Data: An Evaluation of External Validity

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  • BISBEE, JAMES
  • LARSON, JENNIFER M.

Abstract

To answer questions about the origins and outcomes of collective action, political scientists increasingly turn to datasets with social network information culled from online sources. However, a fundamental question of external validity remains untested: are the relationships measured between a person and her online peers informative of the kind of offline, “real-world” relationships to which network theories typically speak? This article offers the first direct comparison of the nature and consequences of online and offline social ties, using data collected via a novel network elicitation technique in an experimental setting. We document strong, robust similarity between online and offline relationships. This parity is not driven by shared identity of online and offline ties, but a shared nature of relationships in both domains. Our results affirm that online social tie data offer great promise for testing long-standing theories in the social sciences about the role of social networks.

Suggested Citation

  • Bisbee, James & Larson, Jennifer M., 2017. "Testing Social Science Network Theories with Online Network Data: An Evaluation of External Validity," American Political Science Review, Cambridge University Press, vol. 111(3), pages 502-521, August.
  • Handle: RePEc:cup:apsrev:v:111:y:2017:i:03:p:502-521_00
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