Abstract

A new method is presented that identifies basic color terms (BCTs) from color-naming data. A function is defined that measures how well a term is understood by a communicating population. BCTs are then separated from other color terms by a threshold value applied to this function. A new mathematical algorithm is proposed and analyzed for determining the best exemplar associated with each BCT. Using data provided by the World Color Survey, comparisons are made between the paper’s methods and those from other studies. These comparisons show that the paper’s new definition of “basicness” mostly agrees with the typical definition found in the color categorization literature, which was originally due to Kay and colleagues. The new definition, unlike the typical one, has the advantage of not relying on syntactic or semantic features of languages or color lexicons. This permits the methodology developed to be generalizable and applied to other category domains for which a construct of “basicness” could have an important role.

© 2017 Optical Society of America

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