1. Predicting Lexical Norms: A Comparison between a Word Association Model and Text-Based Word Co-occurrence Models
- Author
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Simon De Deyne, Steven Verheyen, Gert Storms, and Hendrik Vankrunkelsven
- Subjects
lcsh:Consciousness. Cognition ,Experimental and Cognitive Psychology ,Affect (psychology) ,computer.software_genre ,Semantic data model ,Concreteness ,050105 experimental psychology ,word associations ,03 medical and health sciences ,0302 clinical medicine ,0501 psychology and cognitive sciences ,Valence (psychology) ,concreteness ,business.industry ,k-nearest neighbors ,05 social sciences ,lexical norms ,Co-occurrence ,Replicate ,Word Association ,lcsh:BF309-499 ,Age of Acquisition ,affective word characteristics ,age of acquisition ,Artificial intelligence ,business ,Psychology ,computer ,030217 neurology & neurosurgery ,Natural language processing ,Research Article - Abstract
In two studies we compare a distributional semantic model derived from word co-occurrences and a word association based model in their ability to predict properties that affect lexical processing. We focus on age of acquisition, concreteness, and three affective variables, namely valence, arousal, and dominance, since all these variables have been shown to be fundamental in word meaning. In both studies we use a model based on data obtained in a continued free word association task to predict these variables. In Study 1 we directly compare this model to a word co-occurrence model based on syntactic dependency relations to see which model is better at predicting the variables under scrutiny in Dutch. In Study 2 we replicate our findings in English and compare our results to those reported in the literature. In both studies we find the word association-based model fit to predict diverse word properties. Especially in the case of predicting affective word properties, we show that the association model is superior to the distributional model. ispartof: Journal of Cognition vol:1 issue:1 pages:1-14 ispartof: location:England status: Published online
- Published
- 2018