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

Authors:

Aristides Gionis,

Arno SolinAuthors Info & Claims

WWW '18: Proceedings of the 2018 World Wide Web Conference

Pages 883 - 892

https://doi.org/10.1145/3178876.3186136

Published: 23 April 2018 Publication History

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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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Cited By

Boyd ZCallor NGledhill TJenkins ASnellman RWebb BWonnacott R(2023)The persistent homology of genealogical networksApplied Network Science10.1007/s41109-023-00538-78:1Online publication date: 23-Feb-2023
https://doi.org/10.1007/s41109-023-00538-7
Nockels JGooding PAmes STerras M(2022)Understanding the application of handwritten text recognition technology in heritage contexts: a systematic review of Transkribus in published researchArchival Science10.1007/s10502-022-09397-022:3(367-392)Online publication date: 17-Jun-2022
https://doi.org/10.1007/s10502-022-09397-0
Leskinen PHyvönen E(2021)Reconciling and Using Historical Person Registers as Linked Open Data in the AcademySampo Portal and Data ServiceThe Semantic Web – ISWC 202110.1007/978-3-030-88361-4_42(714-730)Online publication date: 30-Sep-2021
https://doi.org/10.1007/978-3-030-88361-4_42
Show More Cited By

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

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cover image ACM Other conferences

WWW '18: Proceedings of the 2018 World Wide Web Conference

April 2018

2000 pages

ISBN:9781450356398

General Chairs:
Pierre-Antoine Champin
Universitè Claude Bernard Lyon 1, France
,
Fabien Gandon
Inria, Université Côte d'Azur, CNRS, I3S, France
,
Lionel Médini
Université Claude Bernard Lyon 1, France
,
Program Chairs:
Mounia Lalmas
Spotify, UK
,
Panagiotis G. Ipeirotis
New York University, USA

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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IW3C2: International World Wide Web Conference Committee

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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International World Wide Web Conferences Steering Committee

Republic and Canton of Geneva, Switzerland

Publication History

Published: 23 April 2018

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European Commission

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WWW '18

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IW3C2

WWW '18: The Web Conference 2018

April 23 - 27, 2018

Lyon, France

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WWW '18 Paper Acceptance Rate 170 of 1,155 submissions, 15%;

Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

Boyd ZCallor NGledhill TJenkins ASnellman RWebb BWonnacott R(2023)The persistent homology of genealogical networksApplied Network Science10.1007/s41109-023-00538-78:1Online publication date: 23-Feb-2023
https://doi.org/10.1007/s41109-023-00538-7
Nockels JGooding PAmes STerras M(2022)Understanding the application of handwritten text recognition technology in heritage contexts: a systematic review of Transkribus in published researchArchival Science10.1007/s10502-022-09397-022:3(367-392)Online publication date: 17-Jun-2022
https://doi.org/10.1007/s10502-022-09397-0
Leskinen PHyvönen E(2021)Reconciling and Using Historical Person Registers as Linked Open Data in the AcademySampo Portal and Data ServiceThe Semantic Web – ISWC 202110.1007/978-3-030-88361-4_42(714-730)Online publication date: 30-Sep-2021
https://doi.org/10.1007/978-3-030-88361-4_42
Kočí RRozman JZbořil F(2020)Database Concept for Transcription of Registry Records into Digital FormProceedings of the 3rd International Conference on Software Engineering and Information Management10.1145/3378936.3378974(21-25)Online publication date: 12-Jan-2020
https://dl.acm.org/doi/10.1145/3378936.3378974
Kirielle NChristen PRanbaduge T(2019)Outlier Detection Based Accurate Geocoding of Historical AddressesData Mining10.1007/978-981-15-1699-3_4(41-53)Online publication date: 23-Nov-2019
https://doi.org/10.1007/978-981-15-1699-3_4
Zboril FRozman JKoci R(2019)Algorithmic Creation of Genealogical ModelsIntelligent Systems Design and Applications10.1007/978-3-030-16660-1_63(650-658)Online publication date: 14-Apr-2019
https://doi.org/10.1007/978-3-030-16660-1_63

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