title: Insights into failed lexical retrieval from network science.
abstract: Previous network analyses of the phonological lexicon (Vitevitch, 2008) observed a web-like structure that exhibited assortative mixing by degree: words with dense phonological neighborhoods tend to have as neighbors words that also have dense phonological neighborhoods, and words with sparse phonological neighborhoods tend to have as neighbors words that also have sparse phonological neighborhoods. Given the role that assortative mixing by degree plays in network resilience, we examined instances of real and simulated lexical retrieval failures in computer simulations, analysis of a slips-of-the-ear corpus, and three psycholinguistic experiments for evidence of this network characteristic in human behavior. The results of the various analyses support the hypothesis that the structure of words in the mental lexicon influences lexical processing. The implications of network science for current models of spoken word recognition, language processing, and cognitive psychology more generally are discussed.
authors.affiliation: Department of Psychology, University of Kansas, United States. Electronic address: mvitevit@ku.edu.
authors.forename: Michael S
authors.initials: MS
authors.lastname: Vitevitch
authors.affiliation: Department of Psychology, University of Kansas, United States.
authors.forename: Kit Ying
authors.initials: KY
authors.lastname: Chan
authors.affiliation: Department of Psychology, University of Kansas, United States.
authors.forename: Rutherford
authors.initials: R
authors.lastname: Goldstein
mesh_terms: D000328:Adult; D003198:Computer Simulation; D006801:Humans; D011578:Psycholinguistics / Q000379:methods*; D013060:Speech / Q000502:physiology*; D013067:Speech Perception / Q000502:physiology*; D055815:Young Adult
keywords: Mental lexicon; Network science; Spoken word recognition