Analyzing a decade of Colors of the Year

Gijsenij, Arjan; Vazirian, Marjan; Kirchner, Eric; Spiers, Peter; Lai, Peihua; Westland, Stephen; Koeckhoven, Pim

doi:10.1002/col.22566

Cited by 9 publications

(5 citation statements)

References 8 publications

(15 reference statements)

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“…Art paintings are considered to purely reflect the artist’s taste or preference for colours. Essentially, the work is an expression of the artist’s personal aesthetic experience, and diversity is naturally expected, although there are non-personal trends for various styles and articulations that are influenced by social or environmental factors 4 , 5 . Despite the highly personal nature of art paintings, often linked to the notion that ‘ beauty is in the eyes of the beholder ’, there exist art paintings in which different individuals find similar aesthetic pleasure.…”

Section: Introductionmentioning

confidence: 99%

Regularity of colour statistics in explaining colour composition preferences in art paintings

Nakauchi

Tamura

2022

Sci Rep

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This study explores the role of colour statistics in painting preferences and tests the ‘matching-to-nature’ hypothesis which posits that the preference for the colour composition of paintings depends on the extent to which the paintings resemble the colour statistics of natural scenes. A preference judgement experiment was conducted with 31,353 participants using original and hue-rotated versions of 1,200 paintings. Multiple regression analyses were performed between the measured preferences and paintings’ colour statistics to reveal which colour statistics explained the preference data and to what extent. The colour statistics of art paintings that explained the preference data were compared to the colour statistics of natural scenes. The results identified the colour statistics that significantly contributed to explaining painting preferences, and the distributions of the paintings’ colour statistics systematically differed from those of natural scenes. These findings suggest that the human visual system encodes colour statistics to make aesthetic judgements based on the artistic merit of colour compositions, and not on their similarity to natural scenes.

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Section: Introductionmentioning

confidence: 99%

Regularity of colour statistics in explaining colour composition preferences in art paintings

Nakauchi

Tamura

2022

Sci Rep

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“…Our study could also have practical implications for the fashion and marketing communication industries. While the Pantone Color of the Year leads the fashion trend and suggests a relatively fragmented and intensive variation in color trends, 61 our findings show that people's perceptions of basic colors were relatively stable over the last 200 years. Marketing and fashion companies could consider color‐emotion patterns when planning their marketing campaign strategies for the cyclic attention of color stories.…”

Section: Discussionmentioning

confidence: 57%

Have color representations in books changed over the past 200 years? An empirical analysis based on the Google Books Ngram corpus

Guan,

Shi,

et al. 2023

Color Research & Application

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Color significantly shapes our perceptions of the world, and extensive scientific research has explored various aspects of color, including color linguistics, aesthetics, color and marketing, color therapy, and color psychology. Notably, there has been an increasing interest in understanding the psychological domain of color in recent years. However, limited scholarly attention has been given to studying the changes in color representations and emotions over the decades. To address this gap, we utilized word embedding models of Google Books Ngrams corpus to examine the most strongly associated entities and traits with colors and their evolution in color emotions over 200 years. Analyzing three emotional dimensions—pleasure, arousal, and dominance (PAD), we found that red, green, white, black, orange, purple, brown, and pink were related to the exuberant type (+P + A + D) in PAD emotional space. In contrast, blue was linked to the relaxed type (+P−A + D), and yellow constituted the anxious type (−P + A−D). Among all basic English color terms, the emotion‐driven perceptions associated with white, brown, and pink have significantly changed over time.

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“…Meanwhile, if designers can have a design guideline to follow and a reliable database based on big data information of the product to use, it will be better for them to achieve near optimal color design for certain product 3 . Gijsenij et al scholars analyzed the color of the year for paint companies over the past decade and found that analyzing the trends of the color of the year rather than a single color would provide greater help in color design 4 . In order to establish an objective and effective color trends prediction system, researchers have attempted to employ quantitative methods based on past qualitative studies so that explore the trend of popular colors with the help of mathematical models.…”

Section: Introductionmentioning

confidence: 99%

“…3 Gijsenij et al scholars analyzed the color of the year for paint companies over the past decade and found that analyzing the trends of the color of the year rather than a single color would provide greater help in color design. 4 In order to establish an objective and effective color trends prediction system, researchers have attempted to employ quantitative methods based on past qualitative studies so that explore the trend of popular colors with the help of mathematical models. Many research methods and theories have started to be applied to this field by researchers.…”

Section: Introductionmentioning

confidence: 99%

“…Many research methods and theories have started to be applied to this field by researchers. For example, statistical analysis method, [5][6][7] color space analysis, 7 traditional time series model, [8][9][10][11][12][13] neural network, 4,14 etc. These research results have provided important references for the development of quantitative research on popular colors.…”

Section: Introductionmentioning

confidence: 99%

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Color trend prediction method based on genetic algorithm and extreme learning machine

Wang

Liu

Song

et al. 2021

Color Research & Application

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Predicting the trends of future color is a crucial task in the study of color application, which is also of great importance to the business economy and has received increasing attention in the design field in recent years. More advanced quantitative computational methods are expected to make the prediction more accurate, and thus help designers to avoid the interference of subjective factors when carrying out the design. In this article, a hybrid model based on genetic algorithm and extreme learning machine is developed to predict color trends. The accuracy is improved through the optimal solution of hidden bias and input weights of the extreme learning machine searched by a genetic algorithm. By using a real historical dataset of smartphone appearance color, the prediction results of the genetic algorithm‐extreme learning machine model are compared with those of several commonly used models in the past. The accuracy of the model is evaluated in terms of absolute error and mean absolute error values. The results show that the method proposed in this article can maintain higher accuracy when predicting the trends of smartphone appearance color.

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Analyzing a decade of Colors of the Year

Cited by 9 publications

References 8 publications

Regularity of colour statistics in explaining colour composition preferences in art paintings

Regularity of colour statistics in explaining colour composition preferences in art paintings

Have color representations in books changed over the past 200 years? An empirical analysis based on the Google Books Ngram corpus

Color trend prediction method based on genetic algorithm and extreme learning machine

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