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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

A visual example of jointly modeling two social networks: Groom and Aggression.
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pone-0051903-g001: A visual example of jointly modeling two social networks: Groom and Aggression.

Mentions: The basic idea of jointly modeling two binary (un-weighted) networks, corresponding to two types of social behaviors, is to prescribe the probability of a link in one network being associated a link in the other network. Each directed link is encoded as either 0 or 1, so a 2-dimensional binary code represents both directions of the relationship between two nodes. Therefore, the link between every pair of nodes in a two-behavior network is encoded by a 4-dimensional binary code. For example, let the two behaviors be grooming and aggression. A monkey dyad with mutual grooming, but no aggression can be represented by the 4-dimensional code vector (see nodes 2, 3 in Figure 1). A pair of monkeys with opposite directional grooming and aggression is represented by a linkage vector (see nodes 3,4 in Figure 1). Thus, there are 16 possible 4-dimensional linkage vectors, although there are only 10 biologically-distinct vectors. The empirical distribution of these 10 categories of linkage vectors represents the association information between these two behaviors of interest.


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)

A visual example of jointly modeling two social networks: Groom and Aggression.
© Copyright Policy
Related In: Results  -  Collection

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

pone-0051903-g001: A visual example of jointly modeling two social networks: Groom and Aggression.
Mentions: The basic idea of jointly modeling two binary (un-weighted) networks, corresponding to two types of social behaviors, is to prescribe the probability of a link in one network being associated a link in the other network. Each directed link is encoded as either 0 or 1, so a 2-dimensional binary code represents both directions of the relationship between two nodes. Therefore, the link between every pair of nodes in a two-behavior network is encoded by a 4-dimensional binary code. For example, let the two behaviors be grooming and aggression. A monkey dyad with mutual grooming, but no aggression can be represented by the 4-dimensional code vector (see nodes 2, 3 in Figure 1). A pair of monkeys with opposite directional grooming and aggression is represented by a linkage vector (see nodes 3,4 in Figure 1). Thus, there are 16 possible 4-dimensional linkage vectors, although there are only 10 biologically-distinct vectors. The empirical distribution of these 10 categories of linkage vectors represents the association information between these two behaviors of interest.

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