Delphine De Moor, Lauren J. N. Brent, Matthew Silk , Josefine Brask

Animal social structures are remarkably diverse, encompassing relationships that range from strong, lifelong bonds to weaker, more transient connections. Understanding the drivers of this variation is a key question in behavioural ecology and has been the focus of numerous studies linking social structure to ecological, demographic, and life history patterns within groups, populations, and species. Equipped with this information, researchers are now turning to investigations of social structure that are comparative in nature. However, comparing social networks remains a considerable logistical and analytical challenge. Here, we present the layers of latency framework, which outlines how observed social networks are linked to the two underlying latent networks that are of interest for most research questions: the real social network (the actual pattern of social interactions), and the social preferences network driving these interactions. This conceptual framework provides a clear and unified approach to understand when and why differences in network properties and sampling protocols can introduce discrepancies between observed and latent networks, potentially biasing or confounding statistical inference. We then use this conceptual framework to outline some of the central challenges to comparing animal social networks, focusing on differences between networks in behaviour type, sampling effort, sampling type, network size and network scale. For each of these focus points, we describe why and how they create challenges for comparative analyses, and we suggest potential directions for solutions. The layers of latency framework can help researchers to identify networks and features they can (or cannot) compare. In doing so, this framework facilitates advances in cross-species social network studies with the potential to generate new and important insights into the ecological and evolutionary drivers of variation in social structure across the animal kingdom.