Abstract
Since the publication of “Complex Contagions and the Weakness of Long Ties” in 2007, complex contagions have been studied across an enormous variety of social domains. In reviewing this decade of research, we discuss recent advancements in applied studies of complex contagions, particularly in the domains of health, innovation diffusion, social media, and politics. We also discuss how these empirical studies have spurred complementary advancements in the theoretical modeling of contagions, which concern the effects of network topology on diffusion, as well as the effects of individual-level attributes and thresholds. In synthesizing these developments, we suggest three main directions for future research. The first concerns the study of how multiple contagions interact within the same network and across networks, in what may be called an ecology of contagions. The second concerns the study of how the structure of thresholds and their behavioral consequences can vary by individual and social context. The third area concerns the roles of diversity and homophily in the dynamics of complex contagion, including both diversity of demographic profiles among local peers and the broader notion of structural diversity within a network. Throughout this discussion, we make an effort to highlight the theoretical and empirical opportunities that lie ahead.
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Notes
- 1.
Kramer et al.’s study also raised the important point about the ethics of experimentation on social media. While previous social media studies using experimentally designed social platforms [7, 8, 49, 50] enrolled subjects into their online platform with an explicit process of informed consent, Kramer et al.’s study on Facebook used existing networks of peers without their explicit consent. It is an important topic of ongoing discussion how to properly use existing peer networks, such as Facebook and Twitter, to conduct experiments that manipulate user behavior.
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Guilbeault, D., Becker, J., Centola, D. (2018). Complex Contagions: A Decade in Review. In: Lehmann, S., Ahn, YY. (eds) Complex Spreading Phenomena in Social Systems. Computational Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-77332-2_1
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