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

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Journal Title
Journal ISSN
Volume Title
Conference article in proceedings
Date
2018
Major/Subject
Mcode
Degree programme
Language
en
Pages
10
883-892
Series
Proceedings of the International World Wide Web Conference (WWW)
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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Keywords
genealogy, family tree, pedigree, population reconstruction, probabilistic record linkage, assortive mating, social stratification, homogamy
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Citation
Malmi , E , Gionis , A & Solin , A 2018 , Computationally inferred genealogical networks uncover long-term trends in assortative mating . in Proceedings of the International World Wide Web Conference (WWW) . ACM , pp. 883-892 , The Web Conference , Lyon , France , 23/04/2018 . https://doi.org/10.1145/3178876.3186136