The DOI matches its Crossref record; 64 of the 64 references it cites were found in a registry or an index.
The “Small World of Words” English word association norms for over 12,000 cue words
Open accessAbstract
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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Cited by
Brysbaert, M. (2019) · Journal of Cognition · doi:10.5334/joc.72 · Cited by 996
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“…and theory-driven link between continued free association tasks—deriving free associations between concepts—and models based on such data whose network structure could explain aspects of conceptual recall from semantic memory [40,44] or even higher-level phenomena such as problem solving [43].”
BackgroundMethodResultInfluentialEffects of Communication Directionality and AI Agent Differences in Human-AI Interaction
Ashktorab, Z., Dugan, C., Johnson, J., Pan, Q., Zhang, W., Kumaravel, S., & Campbell, M. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445256 · Cited by 50
Differential effects of semantic distance, distractor salience, and relations in verbal analogy
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Metadata
- Authors
- De Deyne, S., Navarro, D. J., Perfors, A., Brysbaert, M., & Storms, G.
- Venue
- Behavior Research Methods
- Published
- 2018-10-08
- Volume
- 51
- Issue
- 3
- Pages
- 987-1006
- ISSN
- 1554-351X (ISSN-L)
- 1554-3528
- OpenAlex
- W2897630418
- Cited by
- 386
- References
- 64
- FWCI
- 39.80
- Type
- journal article
- Language
- en
- Open access
- hybrid
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