Detecting Heterogeneity and Inferring Latent Roles in Longitudinal Networks

Benjamin W. Campbell

Political Analysis, 2018, vol. 26, issue 3, 292-311

Abstract: Network analysis has typically examined the formation of whole networks while neglecting variation within or across networks. These approaches neglect the particular roles actors may adopt within networks. While cross-sectional approaches for inferring latent roles exist, there is a paucity of approaches for considering roles in longitudinal networks. This paper explores the conceptual dynamics of temporally observed roles while deriving and introducing a novel statistical tool, the ego-TERGM, capable of uncovering these latent dynamics. Estimated through an Expectation–Maximization algorithm, the ego-TERGM is quick and accurate in classifying roles within a broader temporal network. An application to the Kapferer strike network illustrates the model’s utility.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:cup:polals:v:26:y:2018:i:03:p:292-311_00

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