Investigation on factors to influence color emotion and color preference responses

Accepted Manuscript Title: Investigation on factors to influence color emotion and color preference responses Authors: Rui Gong, Qing Wang, Yan Hai, Xiaopeng Shao PII: DOI: Reference:

S0030-4026(17)30169-9 http://dx.doi.org/doi:10.1016/j.ijleo.2017.02.026 IJLEO 58842

To appear in: Received date: Accepted date:

20-11-2016 8-2-2017

Please cite this article as: Rui Gong, Qing Wang, Yan Hai, Xiaopeng Shao, Investigation on factors to influence color emotion and color preference responses, Optik - International Journal for Light and Electron Optics http://dx.doi.org/10.1016/j.ijleo.2017.02.026 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Title Investigation on factors to influence color emotion and color preference responses

Author names and affiliations Rui GONG, School of Physics and Optoelectronic Engineering, Xidian University, Xi'an 710071, China Qing WANG, School of Graphic Communication and Packaging Engineering, Qilu University of Technology, Jinan 250353, China Yan HAI, School of Physics and Optoelectronic Engineering, Xidian University, Xi'an 710071, China Xiaopeng SHAO, School of Physics and Optoelectronic Engineering, Xidian University, Xi'an 710071, China

Corresponding author Rui Gong, [email protected]

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Abstract Based on a psychophysical experiment, this study aimed to investigate factors that influenced color emotion and color preference, as well as the correlations between color emotion and color preference. Some color chips of Munsell color order system were picked out to supply actual patterns with different sets to evaluate the factors of hue, chroma, lightness, then they were pasted at a baseplate with black and white backgrounds respectively to involve the influences of backgrounds. Thus, in total 6 groups of color patches were prepared, and 18 attributes were chosen for visual assessment, including 16 words to describe color emotion, together with 2 color preference descriptions, so that massive data of observers’ judgments were gathered. Afterwards, a quantitative analysis and a detailed discussion were carried out for each attribute. Moreover, the calculation of Pearson correlation coefficients indicated that backgrounds could influence the perception of color emotion and color preference in a certain degree, and hue played a more important role than chroma and lightness. Further factor analysis revealed that color emotions do not exist in an isolated manner, and color preference could be represented in three orthogonal dimensions.

Keywords Color emotion, Color preference, Perception psychology, Lighting condition.

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1. Introduction Color is an indispensable element in design that can meet a variety of human needs, which is helpful for the color designers to understand the feelings of the target customers in many industrial fields such as architecture, cosmetology, advertisement, and automobile, etc [1]. Some past studies revealed that human being associates colors with emotion, such as red is exciting and arousing, green is a color for natural and refreshing [2]. Generally, the relevant research efforts have been attracted into two categories, one is the experimental aesthetics, i.e. color preference, such as “like” or “dislike”, and the other one is concerned with the descriptive dimensions of colors such as “heavy” or “light”, “warm” or “cool” [3]. Many scholars endeavored in this field, in which various emotion word pairs of descriptive dimensions and color preference were evaluated, including “like-dislike”, “warm-cool”, “heavy-light”, “active-passive”,

“beautiful-ugly”,

“natural-unnatural”,

“dynamic-static”,

“cheerful-dismal”,

“unstable-stable”, “strong-weak”, “hard-soft”, “transparent-turbid”, “deep-pale”, etc [4-7]. Some of the descriptive dimensions could cause a striking trend on human emotional responses, whereas some dimensions did not shine through. Afterwards, a large number of studies were concentrated on factors that influence color emotion and color preference, in order to seek the potential mechanism between color stimuli and human sensation. So far, the conceivable related factors include the sizes, materials, lighting conditions, backgrounds, surrounds of color stimuli, as well as the gender, age, nationality of observers [8-11], which might influence human’s emotional responses. Though color preference and color emotion are often regarded to be cultural and individual, there are some certain rules and trends. For the influences caused by observation conditions of color stimuli, some scholars analyzed how the texture of color patches affected color emotion [12], observing the color across media (from the glossy paper to a display) may also cause emotional differences [13], and the situation become complicated when color emotion was evaluated in the case of multi-colored image [14]. As for the relationships between color appearance parameters [15] and color emotions, a traditional view point is that hue is the dominant factor, while some studies concluded lightness and chroma play a more important role for most descriptive words except that the “warm-cool” pair that is dependent mainly on hue [16, 17]. Moreover, to represent the effects of factors on color emotion responses, some researchers tried to propose mathematical models for describing the relationships between the observation conditions and emotion responses, which could supply beneficial data and regularities on color emotion and color preference [18-22]. 3

This study was initiated in an attempt to analyses some key factors to influence color emotion and color preference, involving the three color appearance parameters, i.e. hue, chroma, lightness, along with the backgrounds. In the psychophysical experiment, some fundamental descriptive words were employed for the visual evaluation, so that each word of descriptive dimension could be called a perceptual attribute. The color chips of Munsell color order system [23, 24] were adopted because it could supply actual color patterns in a perceptually uniform color space. Afterwards, a quantitative analysis along with a detailed discussion were carried out, in order to develop reasonable rules and models to describe some underline mechanism of human color sensation, which may be helpful for product design. 2. Methods A. Color stimuli The test color stimuli in the visual experiment were picked out according to the Munsell color order system [24], because its basic premise is to specify colors (both psychophysically and physically) with equal visual increments along each of the three perceptual dimensions: hue (H), value (V), and chroma (C). One dimension is the hue circle, which is divided into five principle hues, i.e. purple, blue, green, yellow, and red (denoted 5P, 5B, 5G, 5Y, and 5R), as well as five intermediate hues (designated as 5PB, 5BG, 5GY, 5YR, and 5RP) to form a total of 10 hue names. The dimension of Munsell value (referring to lightness) is divided into 10 main steps of 0~10 from black to white, which could be regarded as a neutral gray dimension (denoted N). In this study, the test color patches were selected from the 10 Munsell hues and the neutral gray, i.e. 5R, 5YR, 5Y, 5GY, 5G, 5BG, 5B, 5PB, 5P, 5RP, and N. The dimension of chroma scale shows equal visual increments from a chroma of 0 for neutral samples to increasing chroma values for samples with stronger hue content. Since the highest chroma values achieved depend on the hue and value of the samples, the visual experiment adopted three combinations of Munsell value and chroma, i.e. V/C sets are 2/3, 6/8, 8/4, respectively, which are accessible for all the selected hues. Figure 1 depicts the hue circle and the value/chroma plane of one constant hue, where the selected V/C sets are marked with red square. The selection of Munsell hue, value, chroma could provide an applicative way to analyze the influences of color appearance factors, i.e. hue, lightness, and chroma. B. Viewing condition Afterwards, each selected V/C set can form a group of 11 colors, consist of 10 hues and the neutral gray. Then each 2.1 cm × 2.1 cm Munsell color chip was pasted at a baseplate with the size of 5.0 cm × 5.0 4

cm to form a test color patch for visual evaluation. The baseplate was made of 2 kinds, black and white, in order to involve the influences of backgrounds. Thus, in total 6 groups of color patches were prepared in the experiment, which were consisted of 3 V/C sets and 2 kinds of background. The experimental geometry is shown in Fig. 2. According to specification of the standard 1931 observer defined by CIE (Commission Internationale de L'Eclairage), the stimuli is ranged from 1° ~ 4° in angular subtense, the background is defined as the environment of the stimulus extending for about 10° from the edge of the stimulus, and the surround is defined as the field outside the background [25]. Accordingly, as the viewing distance was about 30 cm (the comfortable distance for reading), the 2.1 cm × 2.1 cm size of color chips was in response to a viewing angle of 4.0° × 4.0°, and the 5.0 cm × 5.0 cm size of the baseplate corresponded to a viewing angle of 9.5° × 9.5° that could be classified the background in the field of view. In the experiment, each group of color patches would put on a plane in a lighting booth for the observer’s judgments, where the plane was covered by a gray paper with a color close to the Munsell middle gray (N5), which could be regarded as surround in the field of view. A lighting booth of GretagMacbeth SpectraLight III was employed to supply the illumination environment of CIE standard illuminant C [25, 26] with the ambient illumination of about 600 lx (measured in the area of view), since the perceptual uniformity of the Munsell system is only valid under illuminant C with a sufficiently high illuminance level (greater than 500 lx) on a uniform middle gray condition. In the lighting booth, the lower jaw of the observer was fixed by a bracing frame to ensure the viewing distance, and the lighting uniformity was confirmed by measuring different locations of the plane in the lighting booth. C. Evaluated attributes Eight word pairs were employed to describe the color emotion in both English and the native (Chinese) language, i.e. “cute-cool”, “childlike-adult”, “feminine-manlike”, “sweet-bitter”, “pleasant-sorrowful”, “fast-slow”, “rich-cheap”, and “fashionable-not fashionable”, together with the color preference description “like-hate”, as listed in Table 1 (The 9 word pairs are labeled as Q1 ~ Q18 sequentially). For the evaluation, these 18 attributes are descriptive words that were chosen based on a detailed survey of various emotional descriptions from past studies, since they have clear meaning for observers to understand and intuitive feeling linked to color stimuli.

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D. Procedure A panel of 20 observers (10 female and 10 male, ages range from 18 ~ 30) was participated in the psychophysical experiment. All of them have normal vision and normal color vision (via the X-rite Farnsworth-Munsell 100 hue test). The procedure of the visual evaluation is as follows. a) Show one observer a detailed instruction both in English and in Chinese, to help he/she understand the visual task. b) A two-minute dark adaptation and then a one-minute light adaption (using lighting condition in the formal experiment) before the assessments. c) Present one group of 11 color patches (with one given V/C set, 10 hues and the neutral gray) on the plane of the lighting booth, the arrangement of these 11 color patches is at random. The observer was allowed to touch each patch with a pair of gloves. d) The operator would give one word pair of evaluated dimensions (two attributes), the observer was asked to give the most suitable choice and the secondarily suitable choice for each attribute, according to his/her sensation and feeling, then the operator recorded his/her judgment (there are numerical symbols on the back of each patch). e) Change to another word pair, and repeat the step d), record the judgment of the observer. When the evaluations of all the word pairs were finished, one session was completed for one observer. It may cost about 10~15 minutes for one session. f)

Repeat steps c) ~ e) for the other five groups of color patches (different V/C sets and backgrounds) to complete all the sessions. The sequence of the 6 groups shown to the observers was random. There was a five-minute interval for rest and relax between two sessions.

g) Carry out the likewise process for all the 20 observers. 3. Results The experimental scores are processed and shown in Fig. 3, where the 6 group names 2/3B, 6/8B, 8/4B, 2/3W, 6/8W, 8/4W denote the combinations of Munsell V/C sets and backgrounds (“B” denotes black, and “W” means white). In this section, the analysis are based upon a comparison, in which the most suitable choice and the secondarily suitable choice of observers are remarked as “1 score” and “0.5 score” in the data analysis respectively. As can be seen from sub graphs (a) & (b), it seems that warm hues such as 5RP, 5R, 5P could be sorted to the “cute” category, while 5B, 5PB, N obviously belong to the “cool” category. Sub graphs (c) & (d) depict that several hues such as 5YR, 5RP, 5GY, and 5B linked to the “childlike” response. It is 6

worth notice that hue 5P is only reckoned as “childlike” at its low lightness and low chroma. The hues of the “adult” response are N and 5Y, along with 5RP 2/3 and 5PB 8/4. In fact, the hues of 2/3 groups are quite different from those of 6/8 or 8/4, so the emotion of different V/C groups becomes a synthetical response which do not just depend on hue. From sub graphs (e) & (f) it could be concluded that the “feminine-manlike” shows the similar tendency as “cute-cool” does. As shown in sub graphs (g) & (h), the hues which are proximal to red are perceived “sweet”, and the colors with hue N, 5Y, 5GY are considered to be “bitter”, since, from the cultural aspect, 5Y and 5GY colors could be associated with traditional Chinese medicine. The “pleasant” hues are 5YR, 5RP, 5P, 5G, but the 5G 8/4 chip achieves higher score than 5G 2/3 and 5G 6/8. The “sorrowful” hues are 5PB, N, and 5B, as revealed in sub graphs (i) & (j). No visible conclusions can be made for the “fast-slow” response because it may be a little hard for the observers to associate colors with velocity directly in intuition even though “fast-slow” may had something to do with advancing or receding colors. From sub graphs (m) ~ (p), 5GY and 5G are regarded as “cheap” and “not fashionable”, 5P and 5RP are linked to “rich”, and the hues 5P, N, 5PB are “fashionable”. Sub graphs (q) & (r) indicate that to a great extent the color preference is in connection with hue, and obviously the positive emotion such as “sweet”, “pleasant”, “rich”, “fashionable” is often correlated with preferred colors, while the negative descriptions “bitter”, “sorrowful”, “cheap”, “not fashionable” are made from the colors which are often chosen as “hate”. In addition, it is suitable to say that for the responses of “cute”, “feminine”, “sweet” are similar, while “cool”, “manlike”, and “bitter” link to similar responses. The results indicate that people in general perceived positive emotion from the colors which are mostly preferred, while the negative judgments are correlated with the colors which are chosen for “hate”. Based on the external discussion of the experimental data, the following section will continue to explore the rules of the influences of several key factors on color emotion and color preference. 4. Discussions To make a deep quantitative analysis on the influences of several factors on color emotion and color preference, more detailed discussions were carried out on the original judgment data from each observer in the visual experiment. The evaluated factors include the stimuli’s color appearance parameters along with their backgrounds. A. Influences of backgrounds The three V/C sets of 2/3, 6/8, 8/4 were combined with the white and black backgrounds, hence the influences of backgrounds could be analyzed by comparing the data between the two groups with the 7

same V/C set and different backgrounds. Table 2 lists the Pearson correlation coefficient r values [27] between the same colors with black background and with white background. The values of Pearson correlation coefficient are in the range of -1 ~ 1, and the values close to 1 (or -1) depict good relativity between two data sets, where r values larger than 0.5 show some relativity existed. As shown in Table 2, in most cases, the color emotion and color preference of the observers are influenced by the backgrounds to some extent, where most r values are less than 0.7, especially that the “hate” responses of 8/4 group on white background are tremendously different from those of black background. It may be concluded that, stimuli’s backgrounds play a more important role for the colors with higher lightness.

B. Influences of color appearance parameters Table 3 gives the Pearson correlation coefficient r values among color groups with different V/C sets, i.e. the 2/3 and 6/8 sets, the 6/8 and 8/4 sets, and the 8/4 and 2/3 sets, the first row is the data from the two groups with the same V/C set but including both black and white backgrounds, where the second row and the third row involve the data simply with merely one background color ( only black or only white). As can be seen in the table, the color emotion and color preference are influenced by the V/C sets to a certain extent, where most r values are more than 0.7, indicating that for the samples with the same hue, different sets of lightness (V) and chroma (C) could bring about similar responses. Therefore it could be concluded that hue plays a dominant role in color emotion responses compared to lightness and chroma, which is concordant with the traditional view point “hue is the dominant factor to influence color emotion” to some extent, rather than the view point “lightness and chroma play a more important role for most descriptive dimensions” [16, 17]. In addition, the data with only black background show less relativity in comparison to those with only white background, which implies that the black background may result in more influences in color emotion perception than the white background. It might be a common sensation for observers that a color sample viewed with black background would cause stronger visual impact in perceptual feelings than the same color sample with white background, because of the larger contrast between the black and most color samples. Thus, the influences of black background should be considered in the product design. C. Correlations between color emotion and color preference The color preference is very important in applications of color design. Since it is revealed that color preference does have some links to color emotion, this study makes an analysis in this respect. Table 4 8

lists the Pearson correlation coefficient r values between color emotion and color preference responses, in which the r values between each color emotional attribute and the color preference description “like” or “hate” are calculated for all the three V/C sets respectively. In Table 4, as a whole, most r values in the table are in the range of -0.3 ~ 0.3, indicating a little correlation between one single color emotion attribute and the color preference feelings of “like” or “hate”. A possible explanation might be that, though the color preference perception does have some links to color emotion responses, there might be a complicated mechanism of different color emotion attributes to play impacts on color preference, in other words, the judgments of “like” or “hate” by observers may be influenced by several kinds of color emotion descriptions rather than one single color emotion attribute. Moreover, another obvious phenomenon in the table is that, the r values for the “like” and “hate” responses show opposite signs in most cases, it is because of the contrariety between the “like” and “hate” perception, where the influences of color emotion also act on this contrariety. These opposite signs are not fortuitous or by accident. From a certain side, it could be certified that, though the r values show a poor correlation, the influences of color emotion attributes on color preference do exist. D. Interrelationships among different color emotion attributes As the above discussion on Pearson correlation coefficients reveals that color emotions do not exist in an isolated manner, therefore factor analysis [28] was performed, to deeply exam the potential interactions among the different color emotion attributes and to find the important factors affecting the color preference in the color perception of human being. In this process, an extraction method of principle component analysis with varimax rotation was applied to remove redundant (highly correlated) variables from the data, and therefore more compact information could be achieved to describe the color preference in fewer dimensions. In this sense, 16 color emotion attributes (Q1 ~ Q16) were selected as variables, and the input data of each attribute was all the scores for all the color patches. Finally, a threecomponent solution explaining more than 80% variation of the data was selected, and all the 16 variables were reduced to 3 orthogonal dimensions, as shown in Fig. 4. In this figure, components 1, 2, and 3 are defined to describe the largest, the second largest, and the third largest proportions of variations for the whole data, respectively. Moreover, a KMO (Kaiser-Meyer-Olkin) test was also carried out to checkout whether the data were suitable for the implement of factor analysis, and the result score was 0.746, verifying their suitability (results larger than 0.6 could be regarded to be effective in KMO). In Fig. 4(a), it depicts an overall trend, the emotion attributes of odd number (Q1, Q3, Q5,…, Q15) and the attributes of even number (Q2, Q4, Q6,…, Q16) could be sorted into two groups according to 9

their locations in this three-dimensional graph, which indicates that the correlations do exist among different emotion attributes. As a whole, the attributes of odd number and the attributes of even number are usually located in two opposite directions. In Fig. 4 (b) & (d) for the component 1, some emotion word pairs are almost located in the horizontal axis, i.e. “manlike-feminine” and “fast-slow”, and the “rich-poor” word pair also shows large divergence in the horizontal axis, while some emotion word pairs such as “cute-cool”, “pleasantsorrowful”, and “childlike-adult” exhibit little divergence along the horizontal axis, which indicates the component 1 is related to the perceptions whose degree could be described by numbers, e.g. velocity, price, and strength. Thus, it could be concluded that the component 1 should be regarded as “a factor easy to link to a quantitative expression for human being”. Afterwards, in Fig. 4 (b) & (c) for the component 2, “sweet-bitter” and “fashionable-not fashionable” are situated near the axis of the component 2, so it is considered that this component could be described as the commendatory/derogatory aspect of sensation. Besides, in Fig. 4 (c) & (d) for the component 3, “cute-cool” is near the vertical axis of the component 3, and most emotion attributes are nearly in the centrality of each quadrant, meaning that they must be explained by the three components simultaneously, which strongly corroborates they are not independent but correlated, thus the color preference is influenced by several factors. 5. Conclusion In this study, the responses of color emotion and color preference were investigated by a psychophysical experiment. Based on the scores of each word description, the results indicated that positive color emotions were usually from the colors that were mostly preferred, while the negative color emotions were correlated with the colors of “hate”. Moreover, the influences of the backgrounds and color appearance parameters were discussed, and it could be concluded that the backgrounds did influence the perception of color emotion and color preference in a certain degree, and hue played more important impact than chroma and lightness. Besides, the calculation of Pearson correlation coefficients and factor analysis were employed to search the key factors to impact color preference among various color emotion attributes, revealing that color emotions do not exist in an isolated manner, and color preference could be represented in three orthogonal dimensions. Further studies will focus on building mathematical models of color preference based on their correlations with different color emotion descriptions.

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Acknowledgment. This work was supported by the National Natural Science Foundation of China (NSFC) (61505156); and the Fundamental Research Funds for the Central Universities (20101156100).

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[24] Munsell Renotation Data (1929). http://www.rit.edu/cos/colorscience/rc_munsell_renotation.php [25] CIE Publication 15.3. Colorimetry, 3rd Ed. Commission Internationale de L'Eclairage, Vienna (2004). [26] G. Wyszecki, W. S. Stiles, Color Science: Concepts and Methods, Quantitative Data and Formulae, 2nd Edition. John Wiley and Sons, New York, United States (2000). [27] J. A. Schinka, W. F. Velicer, I. B. Weiner, Handbook of Psychology: Research Methods in Psychology, 2nd Edition. John Wiley & Sons, Hoboken, New Jersey, United States (2003). [28] J. M. Lattin, J. D. Carroll, and P. E. Green, Analyzing Multivariate Data. Thomson Learning, United States (2003).

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Figure 1. Graphical representation of (a) hue circle and (b) value/chroma plane of constant hue in the Munsell color order system.

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Figure 2. Experimental geometry of (a) specification of components of the viewing field by CIE and (b) appearance of color patches different backgrounds.

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Figure 3. Color emotion and color preference responses for patches with different backgrounds. 16

Figure 4. Three extracted components by factor analysis.

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Table 1. The word pairs of color emotion and color preference used in the visual experiment. Word pair

Q1 cute Q2 cool

Q3 childlike Q4 adult

Q5 feminine Q6 manlike

Q7 sweet Q8 bitter

Q9 pleasant Q10 sorrowful

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Q11 fast Q12 slow

Q13 rich Q14 cheap

Q15 fashionable Q16 not fashionable

Q17 like Q18 hate

Table 2. The Pearson correlation coefficient r values between color groups with black background and with white background. V/C 2/3 6/8 8/4 V/C 2/3 6/8 8/4

Q1 0.74 0.75 0.74 Q2 0.87 0.88 0.88

Q3 0.77 0.59 0.79 Q4 0.73 0.81 0.78

Q5 0.85 0.86 0.75 Q6 0.81 0.76 0.70

Q7 0.59 0.87 0.88 Q8 0.90 0.87 0.76

Q9 0.61 0.54 0.67 Q10 0.86 0.83 0.84

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Q11 0.62 0.57 0.83 Q12 0.51 0.80 0.70

Q13 0.86 0.86 0.84 Q14 0.78 0.80 0.26

Q15 0.86 0.62 0.73 Q16 0.70 0.75 0.55

Q17 0.57 0.86 0.74 Q18 0.87 0.76 0.49

Table 3. The Pearson correlation coefficient r values among groups with different V/C sets. Backgrounds Black & white Only black Only white

2/3 & 6/8 0.79 0.71 0.77

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6/8 & 8/4 0.80 0.59 0.87

8/4 & 2/3 0.70 0.66 0.74

Table 4. The Pearson correlation coefficient r values between color emotion and color preference responses.

Q17: Like

Q18: Hate

Q17: Like

Q18: Hate

V/C 2/3 6/8 8/4 V/C 2/3 6/8 8/4 V/C 2/3 6/8 8/4 V/C 2/3 6/8 8/4

Q1 0.24 0.13 0.21 Q2 -0.17 -0.18 -0.18 Q1 -0.18 -0.11 -0.15 Q2 0.38 0.48 0.44

Q3 0.29 0.03 0.06 Q4 -0.17 -0.13 -0.14 Q3 0.04 -0.01 0.02 Q4 0.01 -0.12 0.09

Q5 0.26 -0.06 0.03 Q6 -0.10 -0.17 -0.16 Q5 0.11 0.12 0.09 Q6 -0.05 0.09 -0.03

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Q7 0.21 0.07 0.23 Q8 -0.08 -0.14 -0.14 Q7 0.14 0.09 0.03 Q8 -0.08 -0.06 0.01

Q9 0.01 -0.03 -0.03 Q10 -0.14 -0.07 -0.10 Q9 -0.10 -0.09 -0.09 Q10 0.43 0.37 0.28

Q11 0.19 0.09 0.04 Q12 -0.18 -0.14 -0.17 Q11 0.11 -0.01 0.04 Q12 0.04 0.10 0.02

Q13 0.04 0.04 0.04 Q14 -0.11 -0.12 -0.11 Q13 -0.04 -0.01 -0.06 Q14 0.15 0.20 0.20

Q15 0.26 0.13 0.26 Q16 -0.20 -0.15 -0.08 Q15 -0.20 -0.14 -0.18 Q16 0.37 0.40 0.23