Abstract
The paper presents a statistical evaluation of the typological data about color naming systems across the languages of the world that have been obtained by the World Color Survey. In a first step, we discuss a principal component analysis of the categorization data. This leads to a small set of easily interpretable features that are dominant in color categorization. These features were used for a dimensionality reduction of the categorization data. Based on the thus pre-processed data, it is investigated how the participants of the World Color Survey partition the six primary colors black, white, red, green, yellow, and blue into semantic categories. We find a substantial number of counterexamples to the implicative semantic universals that have been suggested in the literature. Finally, an alternative system of semantic universals pertaining to color naming systems is proposed that provides a better fit of the data.
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