| abstract |
| Background According to increase the usage of applications, the popularity of mobile application characters is also increasing day by day. KakaoTalk in Korea, and line applications in Japan are frequently used. The characters used in these applications, Kakao Friends and Line Friends, are all created by Korean designers. In the past, foreign characters were favored, but recently the preference of Korean characters has increased. Therefore, there has been needed for research on the affective estimation of the Korean mobile application character.
Methods This study investigated the features of mobile application characters through the affective estimation, color analysis, SD method, and the factor analysis.
Result Firstly, it was verified that the warm colors with middle chroma and lightness was mainly used through the color analysis. There was no difference between the colors of characters used in Cacao Friends and Line Friends. Secondly, it was confirmed that the factor of 'familiarity' was the most important emotional evaluation factor through the SD method. Thirdly, based on the results of the factor analysis, the characters of Kakao Friends and Line Friends are classified into three categories: 'preference' expressed by expressions and actions, 'motility' based on white color, and 'static' with no facial expression. Lastly, there was the strong correlation between the color of lightness of character's body and the preference factor.
Conclusion The characters were identified that the most important factor was 'familiar' factor. It was possible to infer that the frequency of the character's exposure greatly influences the character's emotional evaluation according to the frequency of the mobile application usage. The results of this study are those of the affective estimation in the basic stage about still images of mobile application characters. Therefore, it is necessary to study the effect of character 's motion and expression on the affective estimation. |
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| Key Words |
| 모바일 애플리케이션, 캐릭터, 감성평가, Mobile Application, Character, Affective Estimation |
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