Network science as a method of measuring language complexity

• Michael Vitevitch ^[1]
  1. [1] University of Kansas

     University of Kansas

     City of Lawrence, Estados Unidos

     
• Localización: Poznan Studies in Contemporary Linguistics, ISSN 1732-0747, ISSN-e 1897-7499, Vol. 50, Nº. 2, 2014 (Ejemplar dedicado a: Special issue on linguistic complexity), págs. 197-205
• Idioma: inglés
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• Resumen

  • The physical, mathematical, and information sciences have developed a number of ways to measure complexity and complex systems in the social, biological, and physical domains. One way of measuring complex systems that might be useful to language scientists is the set of tools from the interdisciplinary field known as network science. A number of studies that have used the tools of network science to examine various aspects of language and language processing are summarized. It is acknowledged that much work must be done to use the tools of network science to address the debate about the (equal) complexity of languages. However, this work may prove useful to language scientists interested in the (equal) complexity of languages, as well as in other topics about language. Furthermore, the distinct structural characteristics observed in networks of several languages to date may also prove useful to network scientists as they try to understand how certain structural characteristics influence network dynamics in other domains. Language scientists are urged to embrace the techniques of network science to address the question of the complexity of languages