Jason Radford
ABSTRACT
Currently, the de facto representational choice for networks is graphs which capture pairwise relationships between entities. This dyadic approach fails to adequate capture the array of group relationships that are more than the sum of their parts and prevalent in real-world situations. For example, collaborative teams, wireless broadcast, and political coalitions all contain unique group dynamics that need to be captured. In this paper, we use simplicial complexes to model these supra-dyadic relationships in networks. We argue that a number of problems within social and communications networks such as network-wide broadcast and collaborative teams can be elegantly captured using simplicial complexes in a way that is not possible with graphs. In this study, we operationalize several types of simplicial complexes in an online-based experiment using the Wildcat Wells paradigm. We then run subjects in these experiments to investigate measures of team strength and hub behavior using simplicial complex models.
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