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Language and Cognition01:27

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Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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Assessing Pressures Shaping Natural Language Lexica.

Jeanne Bruneau-Bongard1,2, Emmanuel Chemla1,3, Thomas Brochhagen2

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Summary
This summary is machine-generated.

Human languages balance informativity and complexity. This study evaluates different complexity measures for linguistic patterns, particularly in color terms, to understand language evolution.

Keywords:
Computational linguisticsInformation theoryLanguage changeLanguage complexitySemantic typology

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Area of Science:

  • Linguistics
  • Cognitive Science
  • Computational Linguistics

Background:

  • Human languages balance communicative informativity and complexity.
  • Existing operationalizations of informativity and complexity, like the Information Bottleneck framework, have limitations in capturing linguistic patterns.
  • The Information Bottleneck framework's notion of complexity has counterintuitive consequences.

Purpose of the Study:

  • To evaluate various operationalizations of complexity in explaining cross-linguistic regularity, focusing on color terms.
  • To propose a method for assessing the explanatory contributions of different complexity measures.
  • To investigate whether complexity and informativity are jointly optimized or in competition.

Main Methods:

  • Analysis of color terms to assess cross-linguistic regularity.
  • Development of a novel method to quantify the explanatory power of different complexity measures.
  • Comparative analysis of complexity definitions within a generalized framework for studying language change.

Main Results:

  • The Information Bottleneck framework's complexity measure has counterintuitive implications for linguistic patterns.
  • Specific notions of complexity significantly contribute to explaining cross-linguistic regularity in color terms.
  • The study provides a framework to empirically adjudicate between competing models of language evolution using data.

Conclusions:

  • Existing complexity measures require refinement to accurately model linguistic phenomena.
  • A data-driven approach is crucial for understanding the forces shaping language change and evolution.
  • The proposed framework offers a more robust method for studying linguistic universals and variation.