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arXiv · 1802.06055

Computationally Inferred Genealogical Networks Uncover Long-Term Trends in Assortative Mating

Eric Malmi·Aristides Gionis·Arno Solin
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Abstract

Genealogical networks, also known as family trees or population pedigrees, are commonly studied by genealogists wanting to know about their ancestry, but they also provide a valuable resource for disciplines such as digital demography, genetics, and computational social science. These networks are typically constructed by hand through a very time-consuming process, which requires comparing large numbers of historical records manually. We develop computational methods for automatically inferring large-scale genealogical networks. A comparison with human-constructed networks attests to the accuracy of the proposed methods. To demonstrate the applicability of the inferred large-scale genealogical networks, we present a longitudinal analysis on the mating patterns observed in a network. This analysis shows a consistent tendency of people choosing a spouse with a similar socioeconomic status, a phenomenon known as assortative mating. Interestingly, we do not observe this tendency to consistently decrease (nor increase) over our study period of 150 years.

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BibTeXRIS

Eric Malmi, Aristides Gionis, Arno Solin. 2018-02-16. Computationally Inferred Genealogical Networks Uncover Long-Term Trends in Assortative Mating. https://arxiv.org/abs/1802.06055

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