Insights into failed lexical retrieval from network science
dc.contributor.author | Vitevitch, Michael S. | |
dc.contributor.author | Chan, Kit Ying | |
dc.contributor.author | Goldstein, Rutherford | |
dc.date.accessioned | 2017-06-08T15:35:37Z | |
dc.date.available | 2017-06-08T15:35:37Z | |
dc.date.issued | 2014-02 | |
dc.identifier.citation | Vitevitch, M. S., Chan, K. Y., & Goldstein, R. (2014). Insights into failed lexical retrieval from network science. Cognitive Psychology, 68, 1–32. http://doi.org/10.1016/j.cogpsych.2013.10.002 | en_US |
dc.identifier.uri | http://hdl.handle.net/1808/24416 | |
dc.description.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. | en_US |
dc.publisher | Elsevier | en_US |
dc.rights | This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License 4.0 (CC BY-NC-ND 4.0), which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | en_US |
dc.subject | Network science | en_US |
dc.subject | Spoken word recognition | en_US |
dc.subject | Mental lexicon | en_US |
dc.title | Insights into failed lexical retrieval from network science | en_US |
dc.type | Article | en_US |
kusw.kuauthor | Vitevitch, Michael S. | |
kusw.kuauthor | Chan, Kit Ying | |
kusw.kuauthor | Goldstein, Rutherford | |
kusw.kudepartment | Psychology | en_US |
dc.identifier.doi | 10.1016/j.cogpsych.2013.10.002 | en_US |
kusw.oaversion | Scholarly/refereed, author accepted manuscript | en_US |
kusw.oapolicy | This item meets KU Open Access policy criteria. | en_US |
dc.identifier.pmid | PMC3891304 | en_US |
dc.rights.accessrights | openAccess |
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Except where otherwise noted, this item's license is described as: This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License 4.0 (CC BY-NC-ND 4.0), which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.