Predicting affinity ties in a surname network.

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 deci...

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Autores principales:	Marcelo Mendoza, Naim Bro
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/0dc752a27f1843c78f6285fa9ba79f8b
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id	oai:doaj.org-article:0dc752a27f1843c78f6285fa9ba79f8b
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spelling	oai:doaj.org-article:0dc752a27f1843c78f6285fa9ba79f8b2021-12-02T20:08:36ZPredicting affinity ties in a surname network.1932-620310.1371/journal.pone.0256603https://doaj.org/article/0dc752a27f1843c78f6285fa9ba79f8b2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0256603https://doaj.org/toc/1932-6203From 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.Marcelo MendozaNaim BroPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 9, p e0256603 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Marcelo Mendoza Naim Bro Predicting affinity ties in a surname network.
description	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.
format	article
author	Marcelo Mendoza Naim Bro
author_facet	Marcelo Mendoza Naim Bro
author_sort	Marcelo Mendoza
title	Predicting affinity ties in a surname network.
title_short	Predicting affinity ties in a surname network.
title_full	Predicting affinity ties in a surname network.
title_fullStr	Predicting affinity ties in a surname network.
title_full_unstemmed	Predicting affinity ties in a surname network.
title_sort	predicting affinity ties in a surname network.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/0dc752a27f1843c78f6285fa9ba79f8b
work_keys_str_mv	AT marcelomendoza predictingaffinitytiesinasurnamenetwork AT naimbro predictingaffinitytiesinasurnamenetwork
_version_	1718375163451408384

Predicting affinity ties in a surname network.

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