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Cited by 894

The DOI matches its Crossref record; 143 of the 143 references it cites were found in a registry or an index.

The representation of abstract words: Why emotion matters.

Kousta, Stavroula-Thaleia, Vigliocco, Gabriella, Vinson, David P., Andrews, Mark, Del Campo, Elena·2011·Journal of Experimental Psychology: General
DOI 10.1037/a0021446
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Abstract

Although much is known about the representation and processing of concrete concepts, knowledge of what abstract semantics might be is severely limited. In this article we first address the adequacy of the 2 dominant accounts (dual coding theory and the context availability model) put forward in order to explain representation and processing differences between concrete and abstract words. We find that neither proposal can account for experimental findings and that this is, at least partly, because abstract words are considered to be unrelated to experiential information in both of these accounts. We then address a particular type of experiential information, emotional content, and demonstrate that it plays a crucial role in the processing and representation of abstract concepts: Statistically, abstract words are more emotionally valenced than are concrete words, and this accounts for a residual latency advantage for abstract words, when variables such as imageability (a construct derived from dual coding theory) and rated context availability are held constant. We conclude with a discussion of our novel hypothesis for embodied abstract semantics.

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Crossref · 10.1037/a0021446

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Metadata

Authors
Kousta, S.-T., Vigliocco, G., Vinson, D. P., Andrews, M., & Del Campo, E.
Venue
Journal of Experimental Psychology: General
Publisher
American Psychological Association (APA)
Published
2011
Volume
140
Issue
1
Pages
14-34
ISSN
  • 0096-3445 (ISSN-L)
  • 1939-2222
DOI
10.1037/a0021446
OpenAlex
W1969138120
Cited by
894
References
143
FWCI
11.59
Type
journal article
Language
en
Open access
closed

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.