The "Small World of Words" English word association norms for over 12,000 cue words.


Journal

Behavior research methods
ISSN: 1554-3528
Titre abrégé: Behav Res Methods
Pays: United States
ID NLM: 101244316

Informations de publication

Date de publication:
06 2019
Historique:
pubmed: 10 10 2018
medline: 19 10 2019
entrez: 10 10 2018
Statut: ppublish

Résumé

Word associations have been used widely in psychology, but the validity of their application strongly depends on the number of cues included in the study and the extent to which they probe all associations known by an individual. In this work, we address both issues by introducing a new English word association dataset. We describe the collection of word associations for over 12,000 cue words, currently the largest such English-language resource in the world. Our procedure allowed subjects to provide multiple responses for each cue, which permits us to measure weak associations. We evaluate the utility of the dataset in several different contexts, including lexical decision and semantic categorization. We also show that measures based on a mechanism of spreading activation derived from this new resource are highly predictive of direct judgments of similarity. Finally, a comparison with existing English word association sets further highlights systematic improvements provided through these new norms.

Identifiants

pubmed: 30298265
doi: 10.3758/s13428-018-1115-7
pii: 10.3758/s13428-018-1115-7
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

987-1006

Auteurs

Simon De Deyne (S)

School of Psychological Sciences, University of Melbourne, 3010, VIC, Australia. simon.dedeyne@unimelb.edu.au.

Danielle J Navarro (DJ)

School of Psychology, University of New South Wales, 2052, NSW, Australia.

Amy Perfors (A)

School of Psychological Sciences, University of Melbourne, 3010, VIC, Australia.

Marc Brysbaert (M)

Department of Psychology, Ghent University, 9000, Ghent, Belgium.

Gert Storms (G)

Department of Psychology, KU Leuven, 3000, Leuven, Belgium.

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Classifications MeSH