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Specificity Ratings for English Data
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A dataset of Specificity ratings for English words is hereby presented, analyzed and discussed in relation with other collections of speaker-generated ratings, including Concreteness. Both, Specificity and Concreteness are analyzed in their ability to explain decision latencies in lexical and semantic tasks, showing important individual contributions. Specificity ratings are collected through Best-Worst scaling method on the words included in the ANEW dataset (Bradley & Lang, 1999), chosen for its compatibility with many other collections of rating resources, and for its comparability with Italian Specificity data (Bolognesi & Caselli, 2023), allowing for cross-linguistic comparisons. Results suggest that Specificity plays an important role in word processing and the importance of taking Specificity into consideration when investigating concreteness effects.
Title: Specificity Ratings for English Data
Description:
A dataset of Specificity ratings for English words is hereby presented, analyzed and discussed in relation with other collections of speaker-generated ratings, including Concreteness.
Both, Specificity and Concreteness are analyzed in their ability to explain decision latencies in lexical and semantic tasks, showing important individual contributions.
Specificity ratings are collected through Best-Worst scaling method on the words included in the ANEW dataset (Bradley & Lang, 1999), chosen for its compatibility with many other collections of rating resources, and for its comparability with Italian Specificity data (Bolognesi & Caselli, 2023), allowing for cross-linguistic comparisons.
Results suggest that Specificity plays an important role in word processing and the importance of taking Specificity into consideration when investigating concreteness effects.
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