The “Small World of Words” English word association norms for over 12,000 cue words
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...
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| Published in | Behavior research methods Vol. 51; no. 3; pp. 987 - 1006 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
15.06.2019
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
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| Abstract | 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. |
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| AbstractList | 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. 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.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. |
| Author | Navarro, Danielle J. Brysbaert, Marc Perfors, Amy De Deyne, Simon Storms, Gert |
| Author_xml | – sequence: 1 givenname: Simon surname: De Deyne fullname: De Deyne, Simon email: simon.dedeyne@unimelb.edu.au organization: School of Psychological Sciences, University of Melbourne – sequence: 2 givenname: Danielle J. surname: Navarro fullname: Navarro, Danielle J. organization: School of Psychology, University of New South Wales – sequence: 3 givenname: Amy surname: Perfors fullname: Perfors, Amy organization: School of Psychological Sciences, University of Melbourne – sequence: 4 givenname: Marc surname: Brysbaert fullname: Brysbaert, Marc organization: Department of Psychology, Ghent University – sequence: 5 givenname: Gert surname: Storms fullname: Storms, Gert organization: Department of Psychology, KU Leuven |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30298265$$D View this record in MEDLINE/PubMed |
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| Title | The “Small World of Words” English word association norms for over 12,000 cue words |
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