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Abstract

Several important recent advances in various sciences (particularly biology and physics) are based on complex network analysis, which provides tools for characterizing statistical properties of networks and explaining how they may arise. This article examines the relevance of this trend for the study of human languages. We review some early efforts to build up language networks, characterize their properties, and show in which direction models are being developed to explain them. These insights are relevant, both for studying fundamental unsolved puzzles in cognitive science, in particular the origins and evolution of language, but also for recent data-driven statistical approaches to natural language.

Keywords: Language, evolution, neural networks, complex networks, syntax

@article{sole05languageNetworks,
  author={Ricard V. Sole and Bernat Corominas and Sergi Valverde and Luc Steels},
  title={Language Networks: their structure, function and evolution},
  journal={Trends in Cognitive Sciences},
  year={2005},
  url={http://www.isrl.uiuc.edu/~amag/langev/paper/sole05languageNetworks.html},
  keywords={Language, evolution, neural networks, complex networks, syntax}
}

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