Using multiplex networks to capture the multidimensional nature of social structure

Sandra E. Smith-Aguilar, Filippo Aureli, Laura Busia, Colleen Schaffner, Gabriel Ramos-Fernández

    Research output: Contribution to journalArticle

    10 Scopus citations


    © 2018, Japan Monkey Centre and Springer Japan KK, part of Springer Nature. Network analysis has increasingly expanded our understanding of social structure in primates and other animal species. However, most studies use networks representing only one interaction type, when social relationships (and the emerging social structure) are the result of many types of interactions and their interplay through time. The recent development of tools facilitating the integrated analysis of multiple interaction types using multiplex networks has opened the possibility of extending the insight provided by social network analysis. We use a multiplex representation of interactions among the members of a group of wild Geoffroy’s spider monkeys (Ateles geoffroyi), to study their social structure. We constructed a six-layered multiplex network based on three indices of overt social interactions (aggression, embraces, grooming) and three distance-based indices (contact, proximity, and association). With tools provided by the MuxViz software, we assessed the relevance of including all six indices in our analysis, the role of individuals in the network (through node versatility), and the presence of modules and non-random triadic structures or motifs. The multiplex provided information which was not equivalent to any individual layer or to the simple aggregation of layers. Network patterns based on associations did not correspond with those observed for overt-interactions or for the multiplex structure. Males were the most versatile individuals, while multiplex modularity and motifs highlighted the relevance of different interaction types for the overall connectivity of the network. We conclude that the multiplex approach improves on previous methods by retaining valuable information from each interaction type and how it is patterned among individuals.
    Original languageAmerican English
    StatePublished - 1 Jan 2018

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