Universality of color names.
We analyzed the World Color Survey (WCS) color-naming data set by using k-means cluster and concordance analyses. Cluster analysis relied on a similarity metric based on pairwise Pearson correlation of the complete chromatic color-naming patterns obtained from individual WCS informants. When K, the number of k-means clusters, varied from 2 to 10, we found that (i) the average color-naming patterns of the clusters all glossed easily to single or composite English patterns, and (ii) the structures of the k-means clusters unfolded in a hierarchical way that was reminiscent of the Berlin and Kay sequence of color category evolution. Gap statistical analysis showed that 8 was the optimal number of WCS chromatic categories: RED, GREEN, YELLOW-OR-ORANGE, BLUE, PURPLE, BROWN, PINK, and GRUE (GREEN-OR-BLUE). Analysis of concordance in color naming within WCS languages revealed small regions in color space that exhibited statistically significantly high concordance across languages. These regions agreed well with five of six primary focal colors of English. Concordance analysis also revealed boundary regions of statistically significantly low concordance. These boundary regions coincided with the boundaries associated with English WARM and COOL. Our results provide compelling evidence for similarities in the mechanisms that guide the lexical partitioning of color space among WCS languages and English.
Lindsey
Delwin T
DT
Department of Psychology, Ohio State University, Mansfield, OH 44906, USA. lindsey.43@osu.edu
Brown
Angela M
AM
D016000:Cluster Analysis; D003116:Color / Q000592:standards*; D014825:Vocabulary