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Ethnicity and Population Structure in Personal Naming Networks

Overview of attention for article published in PLOS ONE, September 2011
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Title
Ethnicity and Population Structure in Personal Naming Networks
Published in
PLOS ONE, September 2011
DOI 10.1371/journal.pone.0022943
Pubmed ID
Authors

Pablo Mateos, Paul A. Longley, David O'Sullivan

Abstract

Personal naming practices exist in all human groups and are far from random. Rather, they continue to reflect social norms and ethno-cultural customs that have developed over generations. As a consequence, contemporary name frequency distributions retain distinct geographic, social and ethno-cultural patterning that can be exploited to understand population structure in human biology, public health and social science. Previous attempts to detect and delineate such structure in large populations have entailed extensive empirical analysis of naming conventions in different parts of the world without seeking any general or automated methods of population classification by ethno-cultural origin. Here we show how 'naming networks', constructed from forename-surname pairs of a large sample of the contemporary human population in 17 countries, provide a valuable representation of cultural, ethnic and linguistic population structure around the world. This innovative approach enriches and adds value to automated population classification through conventional national data sources such as telephone directories and electoral registers. The method identifies clear social and ethno-cultural clusters in such naming networks that extend far beyond the geographic areas in which particular names originated, and that are preserved even after international migration. Moreover, one of the most striking findings of this approach is that these clusters simply 'emerge' from the aggregation of millions of individual decisions on parental naming practices for their children, without any prior knowledge introduced by the researcher. Our probabilistic approach to community assignment, both at city level as well as at a global scale, helps to reveal the degree of isolation, integration or overlap between human populations in our rapidly globalising world. As such, this work has important implications for research in population genetics, public health, and social science adding new understandings of migration, identity, integration and social interaction across the world.

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Geographical breakdown

Country Count As %
France 2 2%
United States 2 2%
Portugal 1 1%
Czechia 1 1%
Denmark 1 1%
United Kingdom 1 1%
China 1 1%
Luxembourg 1 1%
Unknown 86 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 28%
Researcher 14 15%
Student > Master 11 11%
Professor > Associate Professor 6 6%
Student > Doctoral Student 5 5%
Other 20 21%
Unknown 13 14%
Readers by discipline Count As %
Social Sciences 24 25%
Computer Science 15 16%
Medicine and Dentistry 6 6%
Agricultural and Biological Sciences 4 4%
Linguistics 4 4%
Other 27 28%
Unknown 16 17%