A similarity‐based cross‐language comparison of basicness and demarcation of “blue” terms

Abstract

To investigate linguistic and perceptual boundaries within the “blue” region of the color gamut, we analyzed sorting data from speakers of six languages who sorted color stimuli by similarity. Two of these languages, Russian and Italian, are thought to have a separate basic color term and category for “light blue,” distinguishing it from “blue,” and the third was English, which lacks this distinction. There has been less study of the possible basicness of “light blue” terms in the other three languages: Lithuanian and Estonian (both spoken in Baltic states) and Udmurt (a linguistic enclave in North Russia). Sorting data from each sample of speakers were analyzed with principal component analysis and multidimensional scaling, reducing them to a pattern of interstimulus similarities. In addition, color‐naming data were collected for five of the languages and confirmed that sorting responses were not simply a reflection of the words used by subjects to label the stimuli. A “clustering index” was created, quantifying the extent of light/dark blue separation and the strength of any category boundary between them; this was low for English‐language participants but high for Russian and Italian. Udmurt and Lithuanian values were also high, whereas Estonian responses were closer to English. Thus, when clustering of blue stimuli is used as an additional indicator of basicness, the results are compatible with earlier evidence that “light blue” is a separate basic color category in Russian and Italian, and further indicate that light blue terms are basic in Udmurt and Lithuanian, but not Estonian. It may be that “blue” categories are especially susceptible to splitting into two under the influence of linguistic contact. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 362–377, 2017

An online color naming experiment in Russian using Munsell color samples

“…Indeed, in recent years, evidence has been accumulated on the emergence of BCTs beyond the 11 postulated by Berlin and Kay, in particular, linguistic differentiation between light and dark blue in East Slavic and many circum-Mediterranean languages (for a review see ref. 14). Also recently, augmentation of the color inventory was demonstrated for modern British English, with turquoise and lilac considered as emerging BCTs.…”

A cross‐cultural clustering study of similarities and dissimilarities based on concept words cheap, reliable, and high quality and their corresponding color associations

“…In the study, six (Russian, Italian, English, Lithuanian, Estonian, and Udmurt) languages or cultures were considered to investigate the perceptual and linguistic boundaries for the blue region of the color spectrum. The experiment consisted of the subjects from the six languages sorting the color stimuli based on similarity.…”

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“…However, there are very few studies using data mining for automatic knowledge discovery, and hardly any studies that have addressed the concept word-color association using cross-cultural one-way (1-way) clustering as presented in this article. 4,[7][8][9][10][11][12] In an online color-word association survey 13 16 concept words are considered, and 44 possible color choices; including gold, silver, and platinum colors. As per the seminal book 14 picking between a large numbers of choices can cause choice exhaustion, which can prompt subsequent inferior choices.…”

The Influence Of Professional Color Competence On Color Lexicon And Naming Pattern

“…The Russian language possesses rich and nuanced inventory of color terms -the focus of abundant anthropologic, linguistic, and psycholinguistic studies (Apresjan, 2018;Astakhova, 2014;Bimler & Uusküla, 2017;Kalita, 2017;Kezina & Perfilova, 2017;Moss, Davies, Corbett, & Laws, 1990;Shchitova, Shchitov, & Hua, 2018;Stefanov, 2015;Uusküla & Bimler, 2016).…”