Computationally inferred genealogical networks uncover long-term trends in assortative mating

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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.

Details

Original languageEnglish
Title of host publicationProceedings of the International World Wide Web Conference (WWW)
Publication statusPublished - 2018
MoE publication typeA4 Article in a conference publication
EventThe Web Conference - Lyon, France
Duration: 23 Apr 201827 Apr 2018

Conference

ConferenceThe Web Conference
Abbreviated titleWWW
CountryFrance
CityLyon
Period23/04/201827/04/2018

    Research areas

  • genealogy, family tree, pedigree, population reconstruction, probabilistic record linkage, assortive mating, social stratification, homogamy

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