Modeling Bilingual Lexical Processing Through Code-Switching Speech: A Network Science Approach

Qihui Xu, Magdalena Markowska, Martin Chodorow, Ping Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)


The study of code-switching (CS) speech has produced a wealth of knowledge in the understanding of bilingual language processing and representation. Here, we approach this issue by using a novel network science approach to map bilingual spontaneous CS speech. In Study 1, we constructed semantic networks on CS speech corpora and conducted community detections to depict the semantic organizations of the bilingual lexicon. The results suggest that the semantic organizations of the two lexicons in CS speech are largely distinct, with a small portion of overlap such that the semantic network community dominated by each language still contains words from the other language. In Study 2, we explored the effect of clustering coefficients on language choice during CS speech, by comparing clustering coefficients of words that were code-switched with their translation equivalents (TEs) in the other language. The results indicate that words where the language is switched have lower clustering coefficients than their TEs in the other language. Taken together, we show that network science is a valuable tool for understanding the overall map of bilingual lexicons as well as the detailed interconnections and organizations between the two languages.
Original languageEnglish
Article number662409
Number of pages17
JournalFrontiers in Psychology
Publication statusPublished - 25 Aug 2021


  • bilingual lexicon
  • clustering coefficient
  • code-switching speech
  • community detection
  • computational linguistics
  • network science

ASJC Scopus subject areas

  • Psychology(all)


Dive into the research topics of 'Modeling Bilingual Lexical Processing Through Code-Switching Speech: A Network Science Approach'. Together they form a unique fingerprint.

Cite this