Effects of opposition on the diffusion of complex contagions in social networks: an empirical study

Authors:
Chris J. Kuhlman;V. S. Anil Kumar;Madhav V. Marathe;S. S. Ravi;Daniel J. Rosenkrantz
Affiliations:
Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA;Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA;Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA;Computer Science Department, University at Albany-SUNY, Albany, NY;Computer Science Department, University at Albany-SUNY, Albany, NY
Venue:
SBP'11 Proceedings of the 4th international conference on Social computing, behavioral-cultural modeling and prediction
Year:
2011

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Finding critical nodes for inhibiting diffusion of complex contagions in social networks

ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part II

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Abstract

We study the diffusion of complex contagions on social networks in the presence of nodes that oppose the diffusion process. Unlike simple contagions, where a person acquires information or adopts a new ideology based on the influence of a single neighbor, the propagation of complex contagions requires multiple interactions with different neighbors. Our empirical results point out how network structure and opposing perspectives can alter the widespread adoption of social behaviors that can be modeled as complex contagions.