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Joint modeling of multiple social networks to elucidate primate social dynamics: I. maximum entropy principle and network-based interactions.

Chan S, Fushing H, Beisner BA, McCowan B - PLoS ONE (2013)

Bottom Line: Here we develop a bottom-up, iterative modeling approach based upon the maximum entropy principle.Using a rhesus macaque group as a model system, we jointly modeled and analyzed four different social behavioral networks at two different time points (one stable and one unstable) from a rhesus macaque group housed at the California National Primate Research Center (CNPRC).We report and discuss the inter-behavioral dynamics uncovered by our joint modeling approach with respect to social stability.

View Article: PubMed Central - PubMed

Affiliation: Department of Statistics, University of California Davis, Davis, California, USA.

ABSTRACT
In a complex behavioral system, such as an animal society, the dynamics of the system as a whole represent the synergistic interaction among multiple aspects of the society. We constructed multiple single-behavior social networks for the purpose of approximating from multiple aspects a single complex behavioral system of interest: rhesus macaque society. Instead of analyzing these networks individually, we describe a new method for jointly analyzing them in order to gain comprehensive understanding about the system dynamics as a whole. This method of jointly modeling multiple networks becomes valuable analytical tool for studying the complex nature of the interaction among multiple aspects of any system. Here we develop a bottom-up, iterative modeling approach based upon the maximum entropy principle. This principle is applied to a multi-dimensional link-based distributional framework, which is derived by jointly transforming the multiple directed behavioral social network data, for extracting patterns of synergistic inter-behavioral relationships. Using a rhesus macaque group as a model system, we jointly modeled and analyzed four different social behavioral networks at two different time points (one stable and one unstable) from a rhesus macaque group housed at the California National Primate Research Center (CNPRC). We report and discuss the inter-behavioral dynamics uncovered by our joint modeling approach with respect to social stability.

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Related in: MedlinePlus

Empirical networks of the four behaviors for the study group (14B) during the stable time period in 2009.
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pone-0051903-g002: Empirical networks of the four behaviors for the study group (14B) during the stable time period in 2009.

Mentions: We constructed four binary directed networks (i.e. ignoring the frequency/weight of each link) for each of the four behaviors, as show in Fig. 2, using behavioral data collected on group 14B at the CNPRC.


Joint modeling of multiple social networks to elucidate primate social dynamics: I. maximum entropy principle and network-based interactions.

Chan S, Fushing H, Beisner BA, McCowan B - PLoS ONE (2013)

Empirical networks of the four behaviors for the study group (14B) during the stable time period in 2009.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3585323&req=5

pone-0051903-g002: Empirical networks of the four behaviors for the study group (14B) during the stable time period in 2009.
Mentions: We constructed four binary directed networks (i.e. ignoring the frequency/weight of each link) for each of the four behaviors, as show in Fig. 2, using behavioral data collected on group 14B at the CNPRC.

Bottom Line: Here we develop a bottom-up, iterative modeling approach based upon the maximum entropy principle.Using a rhesus macaque group as a model system, we jointly modeled and analyzed four different social behavioral networks at two different time points (one stable and one unstable) from a rhesus macaque group housed at the California National Primate Research Center (CNPRC).We report and discuss the inter-behavioral dynamics uncovered by our joint modeling approach with respect to social stability.

View Article: PubMed Central - PubMed

Affiliation: Department of Statistics, University of California Davis, Davis, California, USA.

ABSTRACT
In a complex behavioral system, such as an animal society, the dynamics of the system as a whole represent the synergistic interaction among multiple aspects of the society. We constructed multiple single-behavior social networks for the purpose of approximating from multiple aspects a single complex behavioral system of interest: rhesus macaque society. Instead of analyzing these networks individually, we describe a new method for jointly analyzing them in order to gain comprehensive understanding about the system dynamics as a whole. This method of jointly modeling multiple networks becomes valuable analytical tool for studying the complex nature of the interaction among multiple aspects of any system. Here we develop a bottom-up, iterative modeling approach based upon the maximum entropy principle. This principle is applied to a multi-dimensional link-based distributional framework, which is derived by jointly transforming the multiple directed behavioral social network data, for extracting patterns of synergistic inter-behavioral relationships. Using a rhesus macaque group as a model system, we jointly modeled and analyzed four different social behavioral networks at two different time points (one stable and one unstable) from a rhesus macaque group housed at the California National Primate Research Center (CNPRC). We report and discuss the inter-behavioral dynamics uncovered by our joint modeling approach with respect to social stability.

Show MeSH
Related in: MedlinePlus