Social network analysis of small social groups: Application of a hurdle GLMM approach in the Alpine marmot ( <i>Marmota marmota</i> )

Social network analysis (SNA) has recently emerged as a fundamental tool to study animal behavior. While many studies have analyzed the relationship between environmental factors and behavior across large, complex populations, few focused on species living in small groups due limitations of statistical methods currently employed. Some difficulties are often comparing social structure different sized accounting for zero-inflation generated by analyzing units. Here, we use case highlight how Generalized Linear Mixed Models (GLMMs) hurdle models can overcome issues inherent metrics that variable size. We applied this approach aggressive Alpine marmot (Marmota marmota) using an eight-year long dataset behavioral interactions 17 family (7.4 ± 3.3 individuals). effect individual group-level aggression, including predictors frequently inferred with larger groups, closely related yellow-bellied flaviventris). Our included GLMMs analyze zero-inflated typical networks groups. Additionally, our results confirmed previously reported effects dominance status aggression levels, thus supporting efficacy approach. found differences males females terms levels roles occupied each agonistic were not predicted socially monogamous species. Finally, provide some perspectives inform subsequent studies.