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The Spatial Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition

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Mapping semantic space: property norms and semantic richness.

Emiko J Muraki¹, David M Sidhu², Penny M Pexman²

¹University of Calgary, Calgary, Canada. ejmuraki@ucalgary.ca.

Cognitive Processing

|September 26, 2019

Summary

The number of features (NoF) influences word processing speed in semantic tasks. Concepts with more features and more shared features facilitate faster responses, confirming NoF

Keywords:

Lexical decision Semantic decision Semantic richness Word recognition

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Area of Science:

Cognitive Psychology
Psycholinguistics
Computational Linguistics

Background:

Variability in the number of features (NoF) for concepts is a known measure of semantic richness.
Previous studies showed that higher NoF and shared features facilitate lexical-semantic task performance.
Prior research was limited by small word sets, often from the McRae norms.

Purpose of the Study:

To test if NoF effects generalize to a larger set of words using new property listing norms.
To explore the relationship between NoF and other semantic richness measures (subjective and objective).
To investigate the structure of semantic richness dimensions.

Main Methods:

Utilized new property listing norms (Buchanan et al., 2019) for a larger item set.
Conducted lexical decision and semantic decision tasks.
Performed factor analyses on various semantic richness measures (e.g., concreteness, imageability, semantic diversity).

Main Results:

Significant NoF effects were found in both lexical and semantic decision tasks.
Words with a higher number of shared features facilitated performance.
Factor analysis revealed distinct clusters of semantic richness dimensions, suggesting embodied and distributional aspects.

Conclusions:

NoF effects are robust and generalize to larger word sets.
Shared features play a significant role in semantic processing.
Semantic representation is multimodal and multidimensional, with distinct embodied and distributional components.