Abstract In group‐living animals, relationships between group members are often highly differentiated. Some dyads can maintain strong and long‐lasting relationships, while others are only connected by weak or fleeting ties. More and more studies show that aspects of social relationships are related to reproductive success and survival. Yet, in the field of animal ecology, few of these studies have considered that frequent or prolonged affiliative interactions between two individuals can be principally driven by two distinct processes: namely, the overall gregariousness of individuals and dyadic affinity, that is, the preference the members of the dyad have to interact specifically with one another. Crucially, these two axes of sociality cannot be observed directly, although distinguishing between them is essential for many research questions, such as when estimating kin bias or studying the link between sociality and fitness. In this work, we present an accessible and principled account of how to estimate these two underlying sociality axes as defined above using dyadic interaction data aimed at animal ecologists. We also provide a lean R package bamoso , which implements models based on the proposed framework and allows visual and numerical evaluation of the estimated sociality axes. We demonstrate critical features of the proposed modelling framework with simulated and empirical data aimed at facilitating understanding of relationships: (1) the possibility of checking model fit against observed data, (2) the assessment of uncertainty in the estimated sociality parameters and (3) the possibility to extend it to more complex models that use interaction data to estimate the relationship between individual‐level social features and individual‐level outcomes in a unified model. Our model provides a simple and principled foundation to explain variation in dyadic interactions, which can be extended to reflect more complex processes using existing modelling frameworks and tools. This approach allows us to address questions about the link between variation in sociality characteristics and other features of interest, both within and across species.
Duboscq et al. (Thu,) studied this question.