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542 – Nonresponse Issues
Link Prediction and Missing Data in Social Network Surveys: An Initial Exploration
Taniecea Arceneaux
U.S. Census Bureau
Burton H. Singer
University of Florida, Emerging Pathogens Institute
An important problem in the analysis of social networks, particularly those modeled using survey response data, is that of non-response. Recent studies have shown the negative effects of missing actors and missing ties on the structural properties of networks [4]. To overcome these problems, we adapt link prediction methodology [6] to the problem of single imputation of item non-response in social network survey data. Empirically, we examine the accuracy of link prediction methods on relational data for social groups in Zablocki's Urban Communes Data Set [13]. Furthermore, we extend the methodology to include the use of supplementary information for link prediction in the case of networks with multiple types of relations on the same individuals.