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How well do similarity measures predict priming in abstract and concrete concepts? /
How well do similarity measures predict priming in abstract and concrete concepts?
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Description: Models of semantic representation predict that automatic priming is determined by associative and co-occurrence relations (i.e., spreading activation accounts), or to similarity in words' semantic features (i.e., featural models). Although, these three factors are correlated in characterizing semantic representation, they seem to tap different aspects of meaning. We designed two lexical decision experiments to dissociate these three different types of meaning similarity. For unmasked primes, we observed priming only due to association strength and not the other two measures; and no evidence for differences in priming for concrete and abstract concepts. For masked primes there was no priming regardless of the semantic relation. These results challenge theoretical accounts of automatic priming. Rather, they are in line with the idea that priming may be due to participants’ controlled strategic processes. These results provide important insight about the nature of priming and how association strength, as determined from word-association norms, relates to the nature of semantic representation.