Ego-Centered Cognitive Social Structures of Close Personal Networks in the United States

Social network analysis is increasingly important in the social and behavioral sciences and has been employed to study a host of inter- and intra-personal social processes. One of the challenges researchers face in this area, however, is balancing the trade-offs between different modes of network measurement and study design. At one end of the spectrum, entirely ego-centered network designs facilitate access to a large, generalizable sample of the population but often lack details on the underlying network structure that embed each respondent. At the other end, whole-network designs offer fine details about the network structure but are costly and suffer from generalizability limitations. In this paper, we employ an ego-centered network sampling design that strikes a balance between these two cases by leveraging how individuals perceive their social worlds vis-a-vis respondent reports of their alter-alter ties. We describe a large sample of close personal networks where respondents informed on their perceptions of the ties between their alters on multiple types of relations. Specifically, we characterize the distribution of network statistics (size, density, and multiplexity) for over a thousand individual ego-centered cognitive networks drawn from a representative sample of the U.S. population. To our knowledge this is the first study to characterize the distribution of mental maps vis-a-vis perceived alter-alter relationships in this large of a sample of respondents involved in close personal networks. In doing so, we more clearly shed light on how Americans perceive the structure of their social worlds and provide an empirical case study in what we characterize as ego-centered cognitive social structures.