Predicting affinity ties in a surname network.
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ABSTRACT:
SUBMITTER: Mendoza M
PROVIDER: S-EPMC8412287 | biostudies-literature | 2021
REPOSITORIES: biostudies-literature
Publications
From administrative registers of last names in Santiago, Chile, we create a surname affinity network that encodes socioeconomic data. This network is a multi-relational graph with nodes representing surnames and edges representing the prevalence of interactions between surnames by socioeconomic decile. We model the prediction of links as a knowledge base completion problem, and find that sharing neighbors is highly predictive of the formation of new links. Importantly, We distinguish between gro ...[more]
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