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Color associations in abstract semantic domains
Douglas Guilbeault1, Ethan O Nadler2, Mark Chu3
1The Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA, USA.
Cognition
|June 7, 2020
Summary
This study reveals that color distributions in image searches for abstract words reflect semantic structure, linking embodied cognition with aesthetic coherence in language.
Area of Science:
- Cognitive Science
- Linguistics
- Computer Science
Background:
- The embodied cognition paradigm explores how sensory experiences shape abstract thought.
- Current research in embodied cognition often relies on textual data, limiting sensory analysis.
- The role of sensory data, like color, in abstract concept semantics is debated.
Purpose of the Study:
- To develop an automated multimodal content analysis method for word-color associations.
- To investigate if color distributions in image search results correlate with semantic structure.
- To synthesize metaphor-based and affect-based theories of embodied semantics.
Main Methods:
- Automated multimodal content analysis of Google Image search results.
- Color measurement using a perceptually uniform colorspace transformation.
- Analysis of word associations across abstract domains (academic disciplines, emotions, music).
- Utilized WordNet and crowdsourced judgments for semantic validation.
Main Results:
- Abstract words cluster significantly based on their associated color distributions.
- Color clustering reflects non-arbitrary semantic structure, supporting embodied cognition.
- More abstract words show higher color variability; semantically similar words share color patterns.
- Color associations reveal shared affective dimensions and aesthetic coherence in language.
Conclusions:
- Color is a significant, non-arbitrary component of abstract concept semantics.
- The findings support embodied cognition by linking sensory data (color) to abstract meaning.
- This approach offers a novel method to integrate metaphor and affect in embodied semantics.
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