Social network analysis of animal behavioral ecology: a cross-discipline approach

Social network analysis (SNA) is a framework used to study the structure of societies. As an umbrella term that encompasses various tools of graph theory and mathematical models to visualize networks, SNA allows researchers to detect and quantify patterns in social networks. Within SNA, individuals are not independent, but are symbiotic or linked with one another in a network. Given its powerful analytical tools, SNA is capable of addressing a range of animal behaviors, and has accordingly become increasingly popular in behavioral ecology studies examining such notions as mate choice/sexual selection, cooperation, information flow and disease transition, behavioral strategies of individuals, fitness consequences of sociality and network stability. Nevertheless, SNA it relatively underutilized among Chinese behavioral ecologists. This study aims at highlighting the benefits of SNA in studying animal behaviors in order to promote greater utilization of SNA within Chinese studies. By first introducing social network theory and demonstrating how social networks can influence individual and collective behaviors, this paper provide a prospective overview of SNA's general utilization for the study of animal behavioral ecology as well as promising directions in the overall use of SNA.