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 grounded neighbors and neighbors in the embedding space, and find that the latter is more predictive of tie formation. The paper discusses the implications of this finding in explaining the high levels of elite endogamy in Santiago.

翻译：基于智利圣地亚哥的姓氏行政登记数据，我们构建了一个编码社会经济信息的姓氏亲和网络。该网络是一个多关系图，节点代表姓氏，边代表按社会经济十分位划分的姓氏间互动的普遍性。我们将链接预测建模为知识库补全问题，发现共享邻居对形成新链接具有高度预测性。重要的是，我们区分了基于图的邻居与嵌入空间中的邻居，并发现后者对链接形成的预测能力更强。本文讨论了这一发现对解释圣地亚哥精英群体内婚制高水平的启示意义。