Many of us “see red,” “feel blue,” or “turn green with envy.” Are such color-emotion associations fundamental to our shared cognitive architecture, or are they cultural creations learned through our languages and traditions? To answer these questions, we tested emotional associations of colors in 4,598 participants from 30 nations speaking 22 native languages. Participants associated 20 emotion concepts with 12 color terms. Pattern-similarity analyses revealed universal color-emotion associations (average similarity coefficient r = .88). However, local differences were also apparent. A machine-learning algorithm revealed that nation predicted color-emotion associations above and beyond those observed universally. Similarity was greater when nations were linguistically or geographically close. This study highlights robust universal color-emotion associations, further modulated by linguistic and geographic factors. These results pose further theoretical and empirical questions about the affective properties of color and may inform practice in applied domains, such as well-being and design.

Russian color naming was explored in a web-based experiment. The purpose was 3-fold: to examine (1) CIELAB coordinates of centroids for 12 Russian basic color terms (BCTs), including 2 Russian terms for "blue", sinij "dark blue", and goluboj "light blue", and compare these with coordinates for the 11 English BCTs obtained in earlier studies; (2) frequent nonBCTs; and (3) gender differences in color naming. Native Russian speakers participated in the experiment using an unconstrained colornaming method. Each participant named 20 colors, selected from 600 colors densely sampling the Munsell Color Solid. Color names and response times of typing onset were registered. Several deviations between centroids of the Russian and English BCTs were found. The 2 "Russian blues", as expected, divided the BLUE area along the lightness dimension; their centroids deviated from a centroid of English blue. Further minor departures were found between centroids of Russian and English counterparts of "brown" and "red". The Russian color inventory confirmed the linguistic refinement of the PURPLE area, with high frequencies of nonBCTs. In addition, Russian speakers revealed elaborated naming strategies and use of a rich inventory of nonBCTs. Elicitation frequencies of the 12 BCTs were comparable for both genders; however, linguistic segmentation of color space, employing a synthetic observer, revealed gender differences in naming colors, with more refined naming of the "warm" colors from females. We conclude that, along with universal perceptual factors, that govern categorical partition of color space, Russian speakers' color naming reflects language-specific factors, supporting the weak relativity hypothesis. K E Y W O R D Scentroids, CIELAB, color naming, color space, gender differences, linguistic segmentation, Russian, webbased experiment | I NT ROD UCTI ONAccording to its color, a visual stimulus is assigned to a certain color category. Identified by a linguistic label (in adult humans), language-specific concepts enable attention to be drawn to certain perceptual attributes of reality. Color names, like other groups of semantically related words, are systems in which one word's position influences the positions of all others.

Hebrew), and Sólveig Þorsteinsdóttir (Icelandic). Finally, we would like to thank all the participants.

The present study is an extension of our analysis of Russian basic color terms (BCTs) elicited in a web‐based psycholinguistic experiment. Color samples (N = 600) were approximately uniformly distributed in the Munsell color solid. An unconstrained color‐naming method was employed. Native Russian speakers (N = 713; 333 males) participated in the study. Among 1422 elicited unique color words, 698 terms (49%) were derived from object names. Here we explore object‐derived non‐BCTs, focusing on broad classes of names referred to objects, categories within these, and the inventory of color terms, as well as their frequency, patterns of derivation, and derivational productivity. Six classes of object referents were identified: flora, fauna, inanimate nature, food and beverages, man‐made objects, body and bodily products. In detail, 20 most frequent object‐derived terms are reported. These are accompanied by analysis of gender differences and representation of the terms' denotata on the Munsell Mercator projection. In addition, Russian object‐derived color terms are related to those in English; discussed are differences between the 2 languages in the color term classes, inventories and incidences. We conclude that Russian object‐derived color terms follow the generic metonymy pattern, that is, signifying color of objects in the speakers' natural environment. The inventory is also language‐specific, reflecting social practices, preferences and views entrenched in the traditional Russian culture. Furthermore, recent extensive development of the inventory signals 2 novel phenomena: marked globalization influence, surfacing as abundant transliteration of English referent loanwords, and noticeable sociolectal diversification that manifests itself by novel evocative color terms, particularly in marketing and advertisement.

The present study is an apparent-time analysis of color terms in Russian native speakers (N = 1927), whose age varied between 16 and 98 years. Stratified sampling was employed with the following age groups: 16–19, 20–29, and so on, with the oldest group of 70 years and over. Color names were elicited in a web-based psycholinguistic experiment (http://colournaming.com). Participants labeled color samples (N = 606) using an unconstrained color-naming method. Color vocabulary of each age group was estimated using multiple linguistic measures: diversity index; frequency of occurrences of 12 Russian basic color terms (BCTs) and of most frequent non-BCTs; color-naming pattern. Our findings show intergenerational differences in Russian color-term vocabulary, color-naming patterns, and object referents. The CT diversity (measured by the Margalef index) progressively increments with speakers’ juniority; the lexical refinement is manifested by the increasing variety of BCT modifiers and growing use of non-BCTs, both traditional and novel. Furthermore, the most frequent Russian non-BCTs sirenevyj “lilac”, salatovyj “lettuce‐colored”, and birûzovyj “turquoise” appear to be the emerging BCTs. The greatest diversity and richness of CT inventory is observed in Russian speakers aged 20–59 years, i.e., those who constitute the active workforce and are enthusiastic consumers. In comparison, speakers of 60 and over manifest less diverse color inventory and greater prevalence of (modified) BCTs. The two youngest groups (16–29 years) are linguistic innovators: their color vocabulary includes abundant recent loanwords, predominantly from English and, not infrequently, CTs as nouns rather than adjectives. Moreover, Generation Z (16–19 years) tend to offer highly specific or idiosyncratic color descriptors that serve expressive rather than informative function. The apprehended dynamics of color naming in apparent time reflects intergenerational differences as such, but even more so dramatic changes of sociocultural reality in the post-Soviet era, whereby Russian speakers, in particular under 60 years, were/are greatly impacted by globalization of trade: new market product arrivals resulted in adoption of novel and elaboration of traditional CTs for efficient communication about perceived color

The purpose of the article is to present an analysis of the studies existing in domestic and foreign science of the necessary age-related "correction" of the color of the educational environment for older people, carried out in respect of the fact that chromatic communication is not limited exclusively to biological reactions, but its structure, in addition to perceptual one, includes much more significant psychological mechanisms and semiotic levels. The selection of research sources was carried out through the RSCI, Google Scholar, Scopus, and Web of Science systems. In total, 63 full texts of articles published between 1999 and 2019 were analyzed. In the process of work, the methods of theoretical and comparative analysis, systematization and generalization of the material were used. The analysis made it possible to distinguish three groups of research. The first group includes works that present the physiological prerequisites for the necessary changes in the chromatic design of the educational space intended for older people. The second group of studies analyzes various aspects of the impact of the color of the educational environment on older people in a psychological connotation. The third group involves the socio-cultural aspects of the formation of the educational environment for older people and analyzes this phenomenon in terms of connection with the lifestyle, way of thinking, physical and emotional-intellectual activity, and social conditions of the aging person. The results of the study convince that color correction in an educational environment designed for older people can cause noticeable changes in the quality of learning at several levels at once – biological (increasing the availability of information and significantly reducing physiological barriers to perception), psychological (supporting and strengthening the processes of memorization and information processing, increasing the psychological comfort of the educational environment), and social (improving the quality of life of older people).

We explored sociolectic differences in color lexicon of Russian speakers. The study aim was twofold: (i) to investigate the influence of growing competence in individuals professionally working with color (henceforth: "color professionals") on the pattern of color names and (ii) to compare color-naming patterns in groups of participants with different levels of professional competence (beginner, intermediate, and advanced). For intergroup comparison, we employed the following indices: (1) frequency of occurrence of recurring color terms; (2) number of words in color descriptors; (3) occurrences of basic color terms (BCTs), monolexemic nonBCTs, and polylexemic BCT-derivatives; and (4) the scope of objects used as color-term referents. An unconstrained color-naming method was used in an online experiment, with total 600 standardized color stimuli presented across respondents. Final dataset contained 48,687 responses of 1,737 native Russian speakers (1,204 females, 526 males), with different levels of color expertise and aged between 16 and 95 years. Results show that both color vocabulary and linguistic patterns of naming color change considerably with respondents' increasing professional experience and expertise. Specifically, the growing color competence is reflected in advanced specificity of naming colors; prevalence of complex patterns of color descriptors that contain greater number of nonBCTs, along with BCTs; greater variety of modifiers and emotionally-laden linguistic components, and professionally-specific object referents, such as dyes, pigments and paint brand names.In the present study we addressed the question of sociolectic differences in color lexicon in Russian native speakers. Purpose of the StudyThe aim of the study was twofold: (i) to investigate influence of experience in individuals working professionally with color (henceforth: "color professionals") on the pattern of color names and (ii) to compare this in groups of participants with different levels of professional competence (beginner, intermediate, and advanced). The intergroup comparison employed the following indices: (1) frequency of occurrence of recurring color terms; (2) number of words in color descriptors; (3) occurrences of BCTs, monolexemic nonBCTs, and BCT-derivatives; and (4) the scope of objects used as color-term referents. Research Methods Design of the web-based experiment procedureAn online data gathering technique was used in the study. Data were collected in a web-based colornaming experiment (Web-based color-naming experiment, n. d.), designed and developed in Adobe Flash CS4 S.V. and ActionScript 3 (Mylonas & MacDonald, 2010). The Flash applet was embedded in HTML and connected via PHP bridges to a mySQL database that sent the test images (color stimuli) in a random order and, in return, stored the information for each participant.The experimental procedure consisted of six steps (Mylonas & MacDonald, 2010. First, observers were asked to adjust their display to RGB settings and adjust brightness, so that all 11 ...

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