Abstract
This chapter provides a discussion of the measurement of individual differences—in particular, personality—in the context of social networks. We highlight some of the ways in which the use of traditional measurement models like IRT may be inappropriate in network data contexts, and why structural network information may offer a useful source of additional information that can be used for measurement. We briefly review some of the various models that have been developed for measuring individual differences in contexts marked by various kinds of interpersonal dependencies. Finally, we develop a new approach to approaching the measurement of individual differences in networks based on exponential random graph models (ERGMs), and demonstrate an application of its use.
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