The aim of this study was to analyze the semantic network structure of keywords and the visual composition of images extracted from Instagram in relation to the multipersona phenomenon with in fashion imagery, which has recently been attracting attention. To this end, the concept of a ‘secondary character’, which forms a separate identity from a ‘main character’ on various social media platforms as well as on the airwaves, was considered as the spread of multi-persona and #SecondaryCharacter on Instagram was investigated. 3,801 keywords were collected after crawling the data using Python and morphological analysis was undertaken using KoNLP. The semantic network structure was then examined by conducting a CONCOR analysis using UCINET and Netdraw to determine the top 50 keywords. The results were then classified into a total of 6 clusters. In accordance with the meaning and context of the keywords included in each cluster, group names were assigned : virtual characters, relationship with the main character, hobbies, daily record, N-job person, media and marketing. Image analysis considered the technical, compositional, and social styles of the media based on Gillian Rose’s visual analysis method. The results determined that Instagram uses fashion images that virtualize one's face to produce multi-persona representation s that show various occupations, describe different types of hobbies, and depict situations pertaining to various social roles.

Abstract
I. Introduction
Ⅱ. Literature Review
    1. Multi-persona and secondary-characters
    2. Instagram and self-presentation
Ⅲ. Methods
    1. Data collection
    2. Data analysis and research process
Ⅳ. Result and Discussion
    1. Content analysis of multi-persona (Hashtag “secondary character”)
    2. Image analysis of multi-persona (Hashtag “secondary character”) fashion image
Ⅴ. Conclusion
References

• Jongsun Kim(서울대학교 의류학과) | 김종선 Corresponding author