An image-based investigation on color associations among 100 Chinese emotion words.

Image data serves as a valuable resource for investigating relationships between colors and emotions. This study conducts an image-based visual corpus analysis on the color associations of 100 Chinese emotion words, aiming to uncover the pivotal roles of colors in understanding emotional concepts. The study addresses two primary objectives: (i) examining the interrelations among four affective properties (valence, arousal, prototypicality, and emotionality) and four image-based color attributes (Jz: a dimension depicting black-white color distinction, Az: a dimension for green-red, Bz: a dimension for blue-yellow, and color variability) associated with these emotion words; and (ii) assessing the efficacy of image-based color information in profiling affective (dis)similarities among different emotion words. The empirical results reveal (i) significant positive correlations between color variability and arousal, Jz and valence, Az and arousal, Bz and valence, as well as a negative correlation between Jz and prototypicality; (ii) the effectiveness of image-based color information in depicting the valence-dominated affective (dis)similarities among the 100 Chinese emotion words. This study contributes image-based empirical support to complement existing research on color-emotion mappings. Moreover, it advances methodological approaches by advocating for the utilisation of image data to address theoretical inquiries in cognitive science.