The Semantic Richness of Abstract Concepts

We contrasted the predictive power of three measures of semantic richness—number of features (NF), 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) facilitate...

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Main Authors: Gabriel eRecchia, Michael eJones
Format: Article
Language:English
Published: Frontiers Media S.A. 2012-11-01
Series:Frontiers in Human Neuroscience
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnhum.2012.00315/full
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spelling doaj-899fd7d455c04b8691f315a38aa531152020-11-25T02:52:27ZengFrontiers Media S.A.Frontiers in Human Neuroscience1662-51612012-11-01610.3389/fnhum.2012.0031536329The Semantic Richness of Abstract ConceptsGabriel eRecchia0Michael eJones1Indiana UniversityIndiana UniversityWe contrasted the predictive power of three measures of semantic richness—number of features (NF), 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, whereas concrete concepts benefit more from rich physical contexts (many associated objects and locations).http://journal.frontiersin.org/Journal/10.3389/fnhum.2012.00315/fullAbstract Conceptsconcretenesslexical decisionSemantic Richnessfeature normscontextual diversity
collection DOAJ
language English
format Article
sources DOAJ
author Gabriel eRecchia
Michael eJones
spellingShingle Gabriel eRecchia
Michael eJones
The Semantic Richness of Abstract Concepts
Frontiers in Human Neuroscience
Abstract Concepts
concreteness
lexical decision
Semantic Richness
feature norms
contextual diversity
author_facet Gabriel eRecchia
Michael eJones
author_sort Gabriel eRecchia
title The Semantic Richness of Abstract Concepts
title_short The Semantic Richness of Abstract Concepts
title_full The Semantic Richness of Abstract Concepts
title_fullStr The Semantic Richness of Abstract Concepts
title_full_unstemmed The Semantic Richness of Abstract Concepts
title_sort semantic richness of abstract concepts
publisher Frontiers Media S.A.
series Frontiers in Human Neuroscience
issn 1662-5161
publishDate 2012-11-01
description We contrasted the predictive power of three measures of semantic richness—number of features (NF), 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, whereas concrete concepts benefit more from rich physical contexts (many associated objects and locations).
topic Abstract Concepts
concreteness
lexical decision
Semantic Richness
feature norms
contextual diversity
url http://journal.frontiersin.org/Journal/10.3389/fnhum.2012.00315/full
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