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dc.contributor.authorLi, ZhaoBin
dc.contributor.authorCrinnion, Anne Marie
dc.contributor.authorMagnuson, James S.
dc.date.accessioned2022-11-30T09:54:03Z
dc.date.available2022-11-30T09:54:03Z
dc.date.issued2022
dc.identifier.citationLi, Z., Crinnion, A.M. & Magnuson, J.S. LexFindR: A fast, simple, and extensible R package for finding similar words in a lexicon. Behav Res 54, 1388–1402 (2022). https://doi.org/10.3758/s13428-021-01667-6es_ES
dc.identifier.citationBehavior Research Methods
dc.identifier.issn1554-351X
dc.identifier.urihttp://hdl.handle.net/10810/58617
dc.descriptionPublished 30 September 2021es_ES
dc.description.abstractLanguage scientists often need to generate lists of related words, such as potential competitors. Theymay do this for purposes of experimental control (e.g., selecting items matched on lexical neighborhood but varying in word frequency), or to test theoretical predictions (e.g., hypothesizing that a novel type of competitor may impact word recognition). Several online tools are available, but most are constrained to a fixed lexicon and fixed sets of competitor definitions, and may not give the user full access to or control of source data. We present LexFindR, an open-source R package that can be easily modified to include additional, novel competitor types. LexFindR is easy to use. Because it can leverage multiple CPU cores and uses vectorized code when possible, it is also extremely fast. In this article, we present an overview of LexFindR usage, illustrated with examples.We also explain the details of how we implemented several standard lexical competitor types used in spoken word recognition research (e.g., cohorts, neighbors, embeddings, rhymes), and show how “lexical dimensions” (e.g., word frequency, word length, uniqueness point) can be integrated into LexFindR workflows (for example, to calculate “frequency-weighted competitor probabilities”), for both spoken and visual word recognition research.es_ES
dc.description.sponsorshipThis work was supported in part by U.S. National Science Foundation grants PAC 1754284 (JM, PI) and IGE NRT 1747486 (JM, PI). The authors are solely responsible for the content of this article. This work was also supported in part by the Basque Government through the BERC 2018-2021 program, and by the Agencia Estatal de Investigaci´on through BCBL Severo Ochoa excellence accreditation SEV-2015-0490.es_ES
dc.language.isoenges_ES
dc.publisherSPRINGERes_ES
dc.relationinfo:eu-repo/grantAgreement/GV/BERC2018-2021es_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/SEV-2015-0490es_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.subjectPsycholinguisticses_ES
dc.subjectLexicones_ES
dc.subjectWord recognitiones_ES
dc.titleLexFindR: A fast, simple, and extensible R package for finding similar words in a lexicones_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder© The Psychonomic Society, Inc. 2021es_ES
dc.relation.publisherversionhttps://www.springer.com/journal/13428es_ES
dc.identifier.doi10.3758/s13428-021-01667-6


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