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

被引:178
|
作者
De Deyne, Simon [1 ]
Navarro, Danielle J. [2 ]
Perfors, Amy [1 ]
Brysbaert, Marc [3 ]
Storms, Gert [4 ]
机构
[1] Univ Melbourne, Sch Psychol Sci, Melbourne, Vic 3010, Australia
[2] Univ New South Wales, Sch Psychol, Sydney, NSW 2052, Australia
[3] Univ Ghent, Dept Psychol, B-9000 Ghent, Belgium
[4] Katholieke Univ Leuven, Dept Psychol, B-3000 Leuven, Belgium
基金
澳大利亚研究理事会;
关键词
Word associations; Mental lexicon; Networks; Similarity; Spreading activation; SEMANTIC NETWORKS; BAYES FACTORS; LARGE SET; BRAIN; SCALE; REPRESENTATIONS; CATEGORIES; STRENGTH; DATABASE; MODELS;
D O I
10.3758/s13428-018-1115-7
中图分类号
B841 [心理学研究方法];
学科分类号
040201 ;
摘要
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.
引用
收藏
页码:987 / 1006
页数:20
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