Literature DB >> 25339692

Extracting information from S-curves of language change.

Fakhteh Ghanbarnejad1, Martin Gerlach2, José M Miotto2, Eduardo G Altmann2.   

Abstract

It is well accepted that adoption of innovations are described by S-curves (slow start, accelerating period and slow end). In this paper, we analyse how much information on the dynamics of innovation spreading can be obtained from a quantitative description of S-curves. We focus on the adoption of linguistic innovations for which detailed databases of written texts from the last 200 years allow for an unprecedented statistical precision. Combining data analysis with simulations of simple models (e.g. the Bass dynamics on complex networks), we identify signatures of endogenous and exogenous factors in the S-curves of adoption. We propose a measure to quantify the strength of these factors and three different methods to estimate it from S-curves. We obtain cases in which the exogenous factors are dominant (in the adoption of German orthographic reforms and of one irregular verb) and cases in which endogenous factors are dominant (in the adoption of conventions for romanization of Russian names and in the regularization of most studied verbs). These results show that the shape of S-curve is not universal and contains information on the adoption mechanism.
© 2014 The Author(s) Published by the Royal Society. All rights reserved.

Keywords:  S-curves; endogenous and exogenous factors; language change

Mesh:

Year:  2014        PMID: 25339692      PMCID: PMC4223929          DOI: 10.1098/rsif.2014.1044

Source DB:  PubMed          Journal:  J R Soc Interface        ISSN: 1742-5662            Impact factor:   4.118


  14 in total

Review 1.  Diversity, competition, extinction: the ecophysics of language change.

Authors:  Ricard V Solé; Bernat Corominas-Murtra; Jordi Fortuny
Journal:  J R Soc Interface       Date:  2010-06-30       Impact factor: 4.118

2.  Endogenous versus exogenous shocks in complex networks: an empirical test using book sale rankings.

Authors:  D Sornette; F Deschâtres; T Gilbert; Y Ageon
Journal:  Phys Rev Lett       Date:  2004-11-22       Impact factor: 9.161

3.  Utterance selection model of language change.

Authors:  G J Baxter; R A Blythe; W Croft; A J McKane
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2006-04-13

4.  Spreading the word.

Authors:  Sandra Knapp; Andrew Polaszek; Mark Watson
Journal:  Nature       Date:  2007-03-15       Impact factor: 49.962

5.  Robust dynamic classes revealed by measuring the response function of a social system.

Authors:  Riley Crane; Didier Sornette
Journal:  Proc Natl Acad Sci U S A       Date:  2008-09-29       Impact factor: 11.205

6.  Quantifying the evolutionary dynamics of language.

Authors:  Erez Lieberman; Jean-Baptiste Michel; Joe Jackson; Tina Tang; Martin A Nowak
Journal:  Nature       Date:  2007-10-11       Impact factor: 49.962

7.  High-accuracy approximation of binary-state dynamics on networks.

Authors:  James P Gleeson
Journal:  Phys Rev Lett       Date:  2011-08-04       Impact factor: 9.161

8.  Seventy-five years of estimating the force of infection from current status data.

Authors:  N Hens; M Aerts; C Faes; Z Shkedy; O Lejeune; P Van Damme; P Beutels
Journal:  Epidemiol Infect       Date:  2009-09-21       Impact factor: 2.451

9.  Word diffusion and climate science.

Authors:  R Alexander Bentley; Philip Garnett; Michael J O'Brien; William A Brock
Journal:  PLoS One       Date:  2012-11-07       Impact factor: 3.240

10.  Internal and external dynamics in language: evidence from verb regularity in a historical corpus of English.

Authors:  Christine F Cuskley; Martina Pugliese; Claudio Castellano; Francesca Colaiori; Vittorio Loreto; Francesca Tria
Journal:  PLoS One       Date:  2014-08-01       Impact factor: 3.240

View more
  7 in total

1.  The dynamics of norm change in the cultural evolution of language.

Authors:  Roberta Amato; Lucas Lacasa; Albert Díaz-Guilera; Andrea Baronchelli
Journal:  Proc Natl Acad Sci U S A       Date:  2018-08-02       Impact factor: 11.205

2.  Text Authorship Identified Using the Dynamics of Word Co-Occurrence Networks.

Authors:  Camilo Akimushkin; Diego Raphael Amancio; Osvaldo Novais Oliveira
Journal:  PLoS One       Date:  2017-01-26       Impact factor: 3.240

3.  Frequency patterns of semantic change: corpus-based evidence of a near-critical dynamics in language change.

Authors:  Q Feltgen; B Fagard; J-P Nadal
Journal:  R Soc Open Sci       Date:  2017-11-08       Impact factor: 2.963

4.  Critical Behaviors in Contagion Dynamics.

Authors:  L Böttcher; J Nagler; H J Herrmann
Journal:  Phys Rev Lett       Date:  2017-02-23       Impact factor: 9.161

5.  A Standardized Project Gutenberg Corpus for Statistical Analysis of Natural Language and Quantitative Linguistics.

Authors:  Martin Gerlach; Francesc Font-Clos
Journal:  Entropy (Basel)       Date:  2020-01-20       Impact factor: 2.524

6.  Large Corpora and Historical Syntax: Consequences for the Study of Morphosyntactic Diffusion in the History of Spanish.

Authors:  Álvaro S Octavio de Toledo Y Huerta
Journal:  Front Psychol       Date:  2019-04-17

7.  The natural selection of words: Finding the features of fitness.

Authors:  Peter D Turney; Saif M Mohammad
Journal:  PLoS One       Date:  2019-01-28       Impact factor: 3.240

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.