Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/44111
Title: Inferring cultural regions from correlation networks of given baby names
Authors: Pomorski, M
Krawczyk, MJ
Kulakowski, K
Kwapien, J
Ausloos, M
First Published: 19-Nov-2015
Publisher: Elsevier for North-Holland
Citation: Physica A: Statistical Mechanics and its Applications, 2016, 445, pp. 169-175 (7)
Abstract: We report investigations on the statistical characteristics of the baby names given between 1910 and 2010 in the United States of America. For each year, the 100 most frequent names in the USA are sorted out. For these names, the correlations between the names profiles are calculated for all pairs of states (minus Hawaii and Alaska). The correlations are used to form a weighted network which is found to vary mildly in time. In fact, the structure of communities in the network remains quite stable till about 1980. The goal is that the calculated structure approximately reproduces the usually accepted geopolitical regions: the North East, the South, and the ”Midwest + West” as the third one. Furthermore, the dataset reveals that the name distribution satisfies the Zipf law, separately for each state and each year, i.e. the name frequency f ∝ r^−α, where r is the name rank. Between 1920 and 1980, the exponent α is the largest one for the set of states classified as ’the South’, but the smallest one for the set of states classified as ”Midwest + West”. Our interpretation is that the pool of selected names was quite narrow in the Southern states. The data is compared with some related statistics of names in Belgium, a country also with different regions, but having quite a different scale than the USA. There, the Zipf exponent is low for young people and for the Brussels citizens.
DOI Link: 10.1016/j.physa.2015.11.003
ISSN: 0378-4371
eISSN: 1873-2119
Links: https://www.sciencedirect.com/science/article/pii/S0378437115009814?via%3Dihub
http://hdl.handle.net/2381/44111
Version: Post-print
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © Elsevier for North-Holland 2015. This version of the paper is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
Appears in Collections:Published Articles, School of Management

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