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dc.contributor.authorDe Deyne, S.en
dc.contributor.authorNavarro, D.en
dc.contributor.authorStorms, G.en
dc.identifier.citationBehavior Research Methods, 2013; 45(2):480-498en
dc.description.abstractIn this article, we describe the most extensive set of word associations collected to date. The database contains over 12,000 cue words for which more than 70,000 participants generated three responses in a multiple-response free association task. The goal of this study was (1) to create a semantic network that covers a large part of the human lexicon, (2) to investigate the implications of a multiple-response procedure by deriving a weighted directed network, and (3) to show how measures of centrality and relatedness derived from this network predict both lexical access in a lexical decision task and semantic relatedness in similarity judgment tasks. First, our results show that the multiple-response procedure results in a more heterogeneous set of responses, which lead to better predictions of lexical access and semantic relatedness than do single-response procedures. Second, the directed nature of the network leads to a decomposition of centrality that primarily depends on the number of incoming links or in-degree of each node, rather than its set size or number of outgoing links. Both studies indicate that adequate representation formats and sufficiently rich data derived from word associations represent a valuable type of information in both lexical and semantic processing.en
dc.description.statementofresponsibilitySimon De Deyne & Daniel J. Navarro & Gert Stormsen
dc.publisherPsychonomic Societyen
dc.rights© Psychonomic Society, Inc. 2012en
dc.subjectWord associations; Semantic network; Lexical decision; Semantic relatedness; Lexical centralityen
dc.titleBetter explanations of lexical and semantic cognition using networks derived from continued rather than single word associationsen
dc.typeJournal articleen
pubs.library.collectionPsychology publicationsen
dc.identifier.orcidNavarro, D. [0000-0001-7648-6578]en
Appears in Collections:Psychology publications

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