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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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Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.
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Modeling Bilingual Lexical Processing Through Code-Switching Speech: A Network Science Approach.

Qihui Xu1, Magdalena Markowska2, Martin Chodorow1,3

  • 1Department of Psychology, Graduate Center, The City University of New York, New York, NY, United States.

Frontiers in Psychology
|September 13, 2021
PubMed
Summary
This summary is machine-generated.

Network science reveals distinct semantic structures in bilingual code-switching (CS) speech. This approach maps bilingual lexicons, showing language-specific organization with some overlap and lower clustering for switched words.

Keywords:
bilingual lexiconclustering coefficientcode-switching speechcommunity detectioncomputational linguisticsnetwork science

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Area of Science:

  • Cognitive Science
  • Computational Linguistics
  • Network Science

Background:

  • Bilingual language processing and representation are significantly informed by the study of code-switching (CS) speech.
  • Understanding the semantic organization and interconnections within bilingual lexicons is crucial for comprehending CS phenomena.

Purpose of the Study:

  • To apply a novel network science approach to map spontaneous bilingual code-switching (CS) speech.
  • To investigate the semantic organization of bilingual lexicons and the influence of network properties on language choice during CS.

Main Methods:

  • Constructed semantic networks from CS speech corpora.
  • Utilized community detection algorithms to analyze semantic organization.
  • Compared clustering coefficients of code-switched words with their translation equivalents (TEs).

Main Results:

  • Semantic networks revealed largely distinct organizations for the two lexicons in CS speech, with some inter-language word overlap within communities.
  • Code-switched words exhibited lower clustering coefficients compared to their translation equivalents in the other language.

Conclusions:

  • Network science offers a valuable framework for mapping bilingual lexicons and understanding the intricate organization of two languages within CS speech.
  • The findings highlight distinct semantic structures and network property differences influencing language choice in bilingual speakers.