Literature DB >> 26069207

Cross-correlations of American baby names.

Paolo Barucca1, Jacopo Rocchi2, Enzo Marinari3, Giorgio Parisi4, Federico Ricci-Tersenghi3.   

Abstract

The quantitative description of cultural evolution is a challenging task. The most difficult part of the problem is probably to find the appropriate measurable quantities that can make more quantitative such evasive concepts as, for example, dynamics of cultural movements, behavioral patterns, and traditions of the people. A strategy to tackle this issue is to observe particular features of human activities, i.e., cultural traits, such as names given to newborns. We study the names of babies born in the United States from 1910 to 2012. Our analysis shows that groups of different correlated states naturally emerge in different epochs, and we are able to follow and decrypt their evolution. Although these groups of states are stable across many decades, a sudden reorganization occurs in the last part of the 20th century. We unambiguously demonstrate that cultural evolution of society can be observed and quantified by looking at cultural traits. We think that this kind of quantitative analysis can be possibly extended to other cultural traits: Although databases covering more than one century (such as the one we used) are rare, the cultural evolution on shorter timescales can be studied due to the fact that many human activities are usually recorded in the present digital era.

Entities:  

Keywords:  clustering; complex systems; cultural evolution; cultural traits

Mesh:

Year:  2015        PMID: 26069207      PMCID: PMC4491744          DOI: 10.1073/pnas.1507143112

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  20 in total

1.  Statistics of atmospheric correlations.

Authors:  M S Santhanam; P K Patra
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2001-06-11

2.  Large scale cross-correlations in Internet traffic.

Authors:  Marc Barthélemy; Bernard Gondran; Eric Guichard
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2002-11-19

3.  Drift as a mechanism for cultural change: an example from baby names.

Authors:  Matthew W Hahn; R Alexander Bentley
Journal:  Proc Biol Sci       Date:  2003-08-07       Impact factor: 5.349

Review 4.  Organization, development and function of complex brain networks.

Authors:  Olaf Sporns; Dante R Chialvo; Marcus Kaiser; Claus C Hilgetag
Journal:  Trends Cogn Sci       Date:  2004-09       Impact factor: 20.229

5.  Random drift and large shifts in popularity of dog breeds.

Authors:  Harold A Herzog; R Alexander Bentley; Matthew W Hahn
Journal:  Proc Biol Sci       Date:  2004-08-07       Impact factor: 5.349

6.  How adoption speed affects the abandonment of cultural tastes.

Authors:  Jonah Berger; Gaël Le Mens
Journal:  Proc Natl Acad Sci U S A       Date:  2009-05-04       Impact factor: 11.205

7.  From Karen to Katie: using baby names to understand cultural evolution.

Authors:  Jonah Berger; Eric T Bradlow; Alex Braunstein; Yao Zhang
Journal:  Psychol Sci       Date:  2012-09-13

8.  The logic of fashion cycles.

Authors:  Alberto Acerbi; Stefano Ghirlanda; Magnus Enquist
Journal:  PLoS One       Date:  2012-03-07       Impact factor: 3.240

9.  Random drift versus selection in academic vocabulary: an evolutionary analysis of published keywords.

Authors:  R Alexander Bentley
Journal:  PLoS One       Date:  2008-08-27       Impact factor: 3.240

10.  Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theory.

Authors:  Feng Luo; Yunfeng Yang; Jianxin Zhong; Haichun Gao; Latifur Khan; Dorothea K Thompson; Jizhong Zhou
Journal:  BMC Bioinformatics       Date:  2007-08-14       Impact factor: 3.169

View more
  4 in total

1.  Inferring processes of cultural transmission: the critical role of rare variants in distinguishing neutrality from novelty biases.

Authors:  James P O'Dwyer; Anne Kandler
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2017-12-05       Impact factor: 6.237

2.  Measuring frequency-dependent selection in culture.

Authors:  Mitchell G Newberry; Joshua B Plotkin
Journal:  Nat Hum Behav       Date:  2022-05-30

Review 3.  Normalization Methods for the Analysis of Unbalanced Transcriptome Data: A Review.

Authors:  Xueyan Liu; Nan Li; Sheng Liu; Jun Wang; Ning Zhang; Xubin Zheng; Kwong-Sak Leung; Lixin Cheng
Journal:  Front Bioeng Biotechnol       Date:  2019-11-26

4.  Network analysis of the social and demographic influences on name choice within the UK (1838-2016).

Authors:  Stephen J Bush; Anna Powell-Smith; Tom C Freeman
Journal:  PLoS One       Date:  2018-10-31       Impact factor: 3.240

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.