헤어커트스타일에 따른 이미지스케일 연구 : 20~30대 미용종사자 중심으로
A Study on Image Scale Based on Haircut Style: Focusing on Beauty Professionals in their 20s and 30s
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Customers visiting hair salons value not only reasonable pricing and service but also design, emotional appeal, and self-image. Therefore, in the hairstyling industry, it is essential to classify image scales based on haircut styles to visually interpret emotions. This study aims to identify emotional vocabulary associated with various haircut styles, enabling designers to better recommend and consult on hairstyles that align with clients' desired images. To analyze the relationship between haircut styles and emotional vocabulary, a survey was conducted with 171 beauty professionals. Based on Yoon Ji-Young's research on beauty-related emotional vocabulary, this study used specific vocabulary for evaluating images according to haircut techniques. The haircut styles were categorized into one length, graduation, and layer, with hair lengths classified as short, medium, and long, and textures as C curl, S curl, and texture curl—resulting in a total of 27 stimuli. Data analysis involved extracting adjectives with the highest frequency of descriptive responses, and text mining was used to assess emotional vocabulary recognition based on haircut techniques. The results of this study suggest that classifying image scales by haircut style can aid in effective client consultations, allowing stylists to propose hairstyles that meet clients' desired images.
Abstract
Customers visiting hair salons value not only reasonable pricing and service but also design, emotional appeal, and self-image. Therefore, in the hairstyling industry, it is essential to classify image scales based on haircut styles to visually interpret emotions. This study aims to identify emotional vocabulary associated with various haircut styles, enabling designers to better recommend and consult on hairstyles that align with clients' desired images. To analyze the relationship between haircut styles and emotional vocabulary, a survey was conducted with 171 beauty professionals. Based on Yoon Ji-Young's research on beauty-related emotional vocabulary, this study used specific vocabulary for evaluating images according to haircut techniques. The haircut styles were categorized into one length, graduation, and layer, with hair lengths classified as short, medium, and long, and textures as C curl, S curl, and texture curl—resulting in a total of 27 stimuli. Data analysis involved extracting adjectives with the highest frequency of descriptive responses, and text mining was used to assess emotional vocabulary recognition based on haircut techniques. The results of this study suggest that classifying image scales by haircut style can aid in effective client consultations, allowing stylists to propose hairstyles that meet clients' desired images.
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