The study of social networks has become widespread in the behavioural sciences. This is largely due to several recent conceptual and analytic advances that enable characterisation of the social fine structure of animal populations [1, 2]. Insights into social network structure have greatly advanced understanding of the dynamics of social processes [3–5] and have provided novel predictions for the evolution of behavioural strategies [6, 7]. However, a common problem of social network studies concerns data collection. For many species, it is often time consuming (and sometimes simply not feasible) to record the interactions among all members of a group or population by direct observation. In some species, interactions are also difficult to observe because the animals are easily disturbed or hard to follow (eg birds and marine mammals). Several technological innovations have the potential to provide a break-through with these issues surrounding data collection. For example, in studies of human social networks, blue-tooth technology via mobile phones has been successfully used to track individuals and their encounter frequencies with others [8]. In non-human animals, tags have been developed that can be deployed to record (or infer) social interactions between individuals (ie the basic building blocks of social networks) based on spatial and/or temporal proximity. Perhaps the simplest tags that can be used for this purpose are PIT (passive integrated transponder) tags, which can be detected by receivers in the environment. For example, PIT tags can be used to record the visits of animals to known food sites (eg bird feeders) or nest boxes and it might be biologically meaningful to record individuals that visit the same location at the same time (or within a short time period) as socially interacting [1].

The technological development with probably the most potential for social network studies is the development of proximity loggers that record the identity of individuals carrying the loggers when they come within a specified distance of one another [9–11]. Over the past decade, this technology has advanced significantly and new-generation proximity loggers weigh so little (1 g) that even small species (such as song-birds) can be fitted with them. The low cost of these tags means that sufficiently large numbers of individuals can be tagged to record the fine details of social patterns in whole groups or populations (eg Encounter Net project; http://encounternet. net/).