Abstract
Every day, millions of people write online restaurant reviews, leave product ratings, provide answers to an unknown user’s question, or contribute lines of code to open-source software, all without any direct reward or recognition. People help strangers offline as well, as when people anonymously donate blood or stop to help a stranded motorist, but these behaviors are relatively rare compared to the pervasiveness of online communities based on user-generated content. Why are mutual-help communities far more common online than in traditional offline settings that are not mediated by the Internet? We address this puzzle in two steps. We begin with empirical evidence from an online experiment that tests two mechanisms for the contagion of helping behavior: “generalized reciprocity” and “third-party influence”. We then use an empirically calibrated agent-based model to show how these mechanisms interact with the rivalness of contributions, that is, the extent to which the benefit from a contribution is limited to just one beneficiary (as when helping a stranded motorist) or benefits many people at once (as when contributing a product review online). The results suggest that the non-rivalness of most user-generated content provides a plausible explanation for the rapid diffusion of helping behavior in online communities.
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Acknowledgements
This work was supported by grants SES-1260348 and SES-1303526 from the National Science Foundation. The first author thanks Scott E. Page, John H. Miller, and participants at the Graduate Workshop in Computational Social Science at the Santa Fe Institute for valuable comments and suggestions.
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Tsvetkova, M., Macy, M. (2015). The Contagion of Prosocial Behavior and the Emergence of Voluntary-Contribution Communities. In: Gonçalves, B., Perra, N. (eds) Social Phenomena. Computational Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-14011-7_7
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DOI: https://doi.org/10.1007/978-3-319-14011-7_7
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