Journal
FRONTIERS IN HUMAN NEUROSCIENCE
Volume 6, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fnhum.2012.00315
Keywords
concreteness; lexical decision; semantic richness; feature norms; abstract concepts
Categories
Funding
- NSF [BCS-1056744]
- Google Research
- Division Of Behavioral and Cognitive Sci
- Direct For Social, Behav & Economic Scie [1056744] Funding Source: National Science Foundation
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We contrasted the predictive power of three measures of semantic richness-number of features (NFs), contextual dispersion (CD), and a novel measure of number of semantic neighbors (NSN)-for a large set of concrete and abstract concepts on lexical decision and naming tasks. NSN (but not NF) facilitated processing for abstract concepts, while NF (but not NSN) facilitated processing for the most concrete concepts, consistent with claims that linguistic information is more relevant for abstract concepts in early processing. Additionally, converging evidence from two datasets suggests that when NSN and CD are controlled for, the features that most facilitate processing are those associated with a concept's physical characteristics and real-world contexts. These results suggest that rich linguistic contexts (many semantic neighbors) facilitate early activation of abstract concepts, where as concrete concepts benefit more from rich physical contexts (many associated objects and locations).
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