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Article: Principles of parametric estimation in modeling language competition

TitlePrinciples of parametric estimation in modeling language competition
Authors
KeywordsFourier's law of heat conduction
Hardy-Weinberg genetic inheritance principle
Lexical diffusion dynamics
Logistic curve
Prestige
Issue Date2013
PublisherNational Academy of Sciences. The Journal's web site is located at http://www.pnas.org
Citation
Proceedings of the National Academy of Sciences of the United States of America, 2013, v. 110 n. 24, p. 9698-9703 How to Cite?
AbstractIt is generally difficult to define reasonable parameters and interpret their values in mathematical models of social phenomena. Rather than directly fitting abstract parameters against empirical data, we should define some concrete parameters to denote the sociocultural factors relevant for particular phenomena, and compute the values of these parameters based upon the corresponding empirical data. Taking the example of modeling studies of language competition, we propose a language diffusion principle and two language inheritance principles to compute two critical parameters, namely the impacts and inheritance rates of competing languages, in our language competition model derived from the Lotka-Volterra competition model in evolutionary biology. These principles assign explicit sociolinguistic meanings to those parameters and calculate their values from the relevant data of population censuses and language surveys. Using four examples of language competition, we illustrate that our language competition model with thus-estimated parameter values can reliably replicate and predict the dynamics of language competition, and it is especially useful in cases lacking direct competition data.
Persistent Identifierhttp://hdl.handle.net/10722/184298
ISSN
2021 Impact Factor: 12.779
2020 SCImago Journal Rankings: 5.011
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZhang, M-
dc.contributor.authorGong, T-
dc.date.accessioned2013-07-05T04:55:21Z-
dc.date.available2013-07-05T04:55:21Z-
dc.date.issued2013-
dc.identifier.citationProceedings of the National Academy of Sciences of the United States of America, 2013, v. 110 n. 24, p. 9698-9703-
dc.identifier.issn0027-8424-
dc.identifier.urihttp://hdl.handle.net/10722/184298-
dc.description.abstractIt is generally difficult to define reasonable parameters and interpret their values in mathematical models of social phenomena. Rather than directly fitting abstract parameters against empirical data, we should define some concrete parameters to denote the sociocultural factors relevant for particular phenomena, and compute the values of these parameters based upon the corresponding empirical data. Taking the example of modeling studies of language competition, we propose a language diffusion principle and two language inheritance principles to compute two critical parameters, namely the impacts and inheritance rates of competing languages, in our language competition model derived from the Lotka-Volterra competition model in evolutionary biology. These principles assign explicit sociolinguistic meanings to those parameters and calculate their values from the relevant data of population censuses and language surveys. Using four examples of language competition, we illustrate that our language competition model with thus-estimated parameter values can reliably replicate and predict the dynamics of language competition, and it is especially useful in cases lacking direct competition data.-
dc.languageeng-
dc.publisherNational Academy of Sciences. The Journal's web site is located at http://www.pnas.org-
dc.relation.ispartofProceedings of the National Academy of Sciences of the United States of America-
dc.subjectFourier's law of heat conduction-
dc.subjectHardy-Weinberg genetic inheritance principle-
dc.subjectLexical diffusion dynamics-
dc.subjectLogistic curve-
dc.subjectPrestige-
dc.titlePrinciples of parametric estimation in modeling language competitionen_US
dc.typeArticleen_US
dc.identifier.emailGong, T: tgong@hku.hk-
dc.description.naturepostprint-
dc.identifier.doi10.1073/pnas.1303108110-
dc.identifier.pmid23716678-
dc.identifier.pmcidPMC3683775-
dc.identifier.scopuseid_2-s2.0-84878988325-
dc.identifier.hkuros222776-
dc.identifier.volume110-
dc.identifier.issue24-
dc.identifier.spage9698-
dc.identifier.epage9703-
dc.identifier.isiWOS:000320930100035-
dc.publisher.placeUnited States-
dc.identifier.issnl0027-8424-

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