Colors evoke similar feelings around the world
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Colors evoke similar feelings around the world

In the current issue of Psychological Science, the scientists report that the participants were asked to fill out an online questionnaire, which involved assigning up to 20 emotions to twelve different color terms
Colors evoke similar feelings around the world

The participants were also asked to specify the intensity with which they associated the color term with the emotion.

The researchers then calculated the national averages for the data and compared these with the worldwide average. "This revealed a significant global consensus," summarized Oberfeld-Twistel. "For example, throughout the world the color of red is the only color that is strongly associated with both a positive feeling -- love -- and a negative feeling -- anger." Brown, on the other hand, triggers the fewest emotions globally. However, the scientists also noted some national peculiarities. For example, the color of white is much more closely associated with sadness in China than it is in other countries, and the same applies to purple in Greece. "This may be because in China white clothing is worn at funerals and the color dark purple is used in the Greek Orthodox Church during periods of mourning," explained Oberfeld-Twistel. In addition to such cultural peculiarities, the climate may also play a role. According to the findings from another of the team's studies, yellow tends to be more closely associated with the emotion of joy in countries that see less sunshine, while the association is weaker in areas that have greater exposure to it. According to Dr. Daniel Oberfeld-Twistel, it is currently difficult to say exactly what the causes for global similarities and differences are. "There is a range of possible influencing factors: language, culture, religion, climate, the history of human development, the human perceptual system." Many fundamental questions about the mechanisms of color-emotion associations have yet to be clarified, he continued. However, by using an in-depth analysis that included the use of a machine learning approach developed by Oberfeld-Twistel, a computer program that improves itself as the database grows, the scientists have already discovered that the differences between individual nations are greater the more they are geographically separated and/or the greater the differences between the languages spoken in them.

Read the full article at the original website

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