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Network diffusion of competing behaviors

Journal of Computational Social Science volume 5, pages 47–68 (2022)Cite this article

Abstract

Research indicates that network structure affects the diffusion of a single behavior. However, in many social settings, two or more behaviors may compete for adoption, as in the case of religious competition, social movements and counter-movements, or conflicting rumors. Lessons from one-behavior diffusion cannot be easily applied because the outcome can take the form of one-behavior domination, two behaviors splitting the network, both behaviors occupying a small fraction of the network, or no diffusion. This article tests how three well-known factors of single-behavior diffusion—network transitivity, adoption threshold, and connectedness of early adopters—apply to scenarios of competitive diffusion. Results show that minor differences in initial adopter size tend to magnify, creating a significant “head-start advantage.” Nevertheless, the degree of this advantage depends on the interaction between network transitivity, adoption threshold, and connectedness of initial adopters. The article describes the conditions under which countervailing ties may (or may not) create inequality in behavioral diffusion.

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Fig. 1
Fig. 2

Availability of data and material (data transparency)

Not applicable: this is a simulation study

Code availability

Available in supplementary file.

Notes

  1. I use the term behavior in relation to a wide range of adoption phenomena, such as using technology, wearing a particular fashion item, joining a collective action, and practicing a religion. The key notion is that the behavior is a dichotomous choice: one can either adopt or not adopt.

  2. There are many ways to consider the connectedness of initial adopters. In this article, I connect them as a connected component where all initial adopters are connected as one group through social relationships. Also see section on experiment design.

  3. This is equivalent to “rewiring” the network.

  4. These examples are broadly illustrative rather than strictly true for each case. For instance, although transitivity is generally low in social media networks, it may be high for the social media pages of certain groups where users connect more (e.g., support pages for patients with the same disease).

  5. This refers to the probability of deleting ties from the original network and replacing them with new random ties.

  6. Actors may adopt different behaviors or none at different iterations.

  7. I assume the same threshold and setup of early adopters for both behaviors, rendering the behaviors substitutable.

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  1. Department of Sociology, Department of Statistics, University of Washington, 211 Savery Hall, Box 353340, Seattle, WA, 98195-3340, USA

    Yuan Hsiao

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Hsiao, Y. Network diffusion of competing behaviors. J Comput Soc Sc 5, 47–68 (2022). https://doi.org/10.1007/s42001-021-00115-x

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Keywords

  • Competitive diffusion
  • Behavioral adoption
  • Social networks
  • Simulations