A multiplex centrality metric for complex social networks: sex, social status, and family structure predict multiplex centrality in rhesus macaques
Members of a society interact using a variety of social behaviors, giving rise to a multi-faceted and complex social life. For the study of animal behavior, quantifying this complexity is critical for understanding the impact of social life on animals’ health and fitness. Multilayer network approach...
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doaj-3714951e9ed7443292cfaa78d4ba747b2020-11-25T02:38:14ZengPeerJ Inc.PeerJ2167-83592020-03-018e871210.7717/peerj.8712A multiplex centrality metric for complex social networks: sex, social status, and family structure predict multiplex centrality in rhesus macaquesBrianne Beisner0Niklas Braun1Márton Pósfai2Jessica Vandeleest3Raissa D’Souza4Brenda McCowan5Department of Population Health & Reproduction, School of Veterinary Medicine, University of California, Davis, Davis, CA, United States of AmericaDepartment of Mechanical and Aerospace Engineering, University of California, Davis, Davis, CA, United States of AmericaDepartment of Computer Sciences, University of California, Davis, Davis, CA, United States of AmericaNeuroscience and Behavior Unit, California National Primate Research Center, Davis, CA, United States of AmericaDepartment of Mechanical and Aerospace Engineering, University of California, Davis, Davis, CA, United States of AmericaDepartment of Population Health & Reproduction, School of Veterinary Medicine, University of California, Davis, Davis, CA, United States of AmericaMembers of a society interact using a variety of social behaviors, giving rise to a multi-faceted and complex social life. For the study of animal behavior, quantifying this complexity is critical for understanding the impact of social life on animals’ health and fitness. Multilayer network approaches, where each interaction type represents a different layer of the social network, have the potential to better capture this complexity than single layer approaches. Calculating individuals’ centrality within a multilayer social network can reveal keystone individuals and more fully characterize social roles. However, existing measures of multilayer centrality do not account for differences in the dynamics and functionality across interaction layers. Here we validate a new method for quantifying multiplex centrality called consensus ranking by applying this method to multiple social groups of a well-studied nonhuman primate, the rhesus macaque. Consensus ranking can suitably handle the complexities of animal social life, such as networks with different properties (sparse vs. dense) and biological meanings (competitive vs. affiliative interactions). We examined whether individuals’ attributes or socio-demographic factors (sex, age, dominance rank and certainty, matriline size, rearing history) were associated with multiplex centrality. Social networks were constructed for five interaction layers (i.e., aggression, status signaling, conflict policing, grooming and huddling) for seven social groups. Consensus ranks were calculated across these five layers and analyzed with respect to individual attributes and socio-demographic factors. Generalized linear mixed models showed that consensus ranking detected known social patterns in rhesus macaques, showing that multiplex centrality was greater in high-ranking males with high certainty of rank and females from the largest families. In addition, consensus ranks also showed that females from very small families and mother-reared (compared to nursery-reared) individuals were more central, showing that consideration of multiple social domains revealed individuals whose social centrality and importance might otherwise have been missed.https://peerj.com/articles/8712.pdfMultilayer networksAnimal behaviorComplex societiesNetwork analysisSocial behaviorNonhuman primates |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Brianne Beisner Niklas Braun Márton Pósfai Jessica Vandeleest Raissa D’Souza Brenda McCowan |
spellingShingle |
Brianne Beisner Niklas Braun Márton Pósfai Jessica Vandeleest Raissa D’Souza Brenda McCowan A multiplex centrality metric for complex social networks: sex, social status, and family structure predict multiplex centrality in rhesus macaques PeerJ Multilayer networks Animal behavior Complex societies Network analysis Social behavior Nonhuman primates |
author_facet |
Brianne Beisner Niklas Braun Márton Pósfai Jessica Vandeleest Raissa D’Souza Brenda McCowan |
author_sort |
Brianne Beisner |
title |
A multiplex centrality metric for complex social networks: sex, social status, and family structure predict multiplex centrality in rhesus macaques |
title_short |
A multiplex centrality metric for complex social networks: sex, social status, and family structure predict multiplex centrality in rhesus macaques |
title_full |
A multiplex centrality metric for complex social networks: sex, social status, and family structure predict multiplex centrality in rhesus macaques |
title_fullStr |
A multiplex centrality metric for complex social networks: sex, social status, and family structure predict multiplex centrality in rhesus macaques |
title_full_unstemmed |
A multiplex centrality metric for complex social networks: sex, social status, and family structure predict multiplex centrality in rhesus macaques |
title_sort |
multiplex centrality metric for complex social networks: sex, social status, and family structure predict multiplex centrality in rhesus macaques |
publisher |
PeerJ Inc. |
series |
PeerJ |
issn |
2167-8359 |
publishDate |
2020-03-01 |
description |
Members of a society interact using a variety of social behaviors, giving rise to a multi-faceted and complex social life. For the study of animal behavior, quantifying this complexity is critical for understanding the impact of social life on animals’ health and fitness. Multilayer network approaches, where each interaction type represents a different layer of the social network, have the potential to better capture this complexity than single layer approaches. Calculating individuals’ centrality within a multilayer social network can reveal keystone individuals and more fully characterize social roles. However, existing measures of multilayer centrality do not account for differences in the dynamics and functionality across interaction layers. Here we validate a new method for quantifying multiplex centrality called consensus ranking by applying this method to multiple social groups of a well-studied nonhuman primate, the rhesus macaque. Consensus ranking can suitably handle the complexities of animal social life, such as networks with different properties (sparse vs. dense) and biological meanings (competitive vs. affiliative interactions). We examined whether individuals’ attributes or socio-demographic factors (sex, age, dominance rank and certainty, matriline size, rearing history) were associated with multiplex centrality. Social networks were constructed for five interaction layers (i.e., aggression, status signaling, conflict policing, grooming and huddling) for seven social groups. Consensus ranks were calculated across these five layers and analyzed with respect to individual attributes and socio-demographic factors. Generalized linear mixed models showed that consensus ranking detected known social patterns in rhesus macaques, showing that multiplex centrality was greater in high-ranking males with high certainty of rank and females from the largest families. In addition, consensus ranks also showed that females from very small families and mother-reared (compared to nursery-reared) individuals were more central, showing that consideration of multiple social domains revealed individuals whose social centrality and importance might otherwise have been missed. |
topic |
Multilayer networks Animal behavior Complex societies Network analysis Social behavior Nonhuman primates |
url |
https://peerj.com/articles/8712.pdf |
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