빅데이터 분석을 활용한 시니어 패션의 인식 변화에 대한 연구 (An Analysis of the Change in Perception of Senior Fashion Using Big Data Analysis)

서지정보

· 발행기관 : 한국복식학회
· 수록지 정보 : 복식 / 74권 / 4호 / 130 ~ 150페이지
· 저자명 : 강유림, 김문영

초록

To understand the flow and issues associated with changes in the social perception of senior fashion through big data analysis, this study first identified important keywords and overall trends related to senior fashion. Second, the use of senior fashion through clusters was investigated, and third, the process of changing emotions towards senior fashion keywords was investigated. Using Textom, big data on senior fashion were collected for two periods: from January 1, 2014 to December 31, 2018 and from January 1, 2019 to December 31, 2023. To analyze the data, text mining techniques, CONCOR analysis, and emotion analysis were conducted. The results of this study are as follows: First, through text mining, we established that the core keywords of senior fashion from 2014 to 2018 were 'senior', 'fashion', 'model', 'fashion show', 'clothes', and 'culture', and those from 2019 to 2023 were 'model', 'senior', 'fashion show', 'class', and 'fashion'. Second, as a result of the CONCOR analysis, five clusters were derived from 2014 to 2018 and four from 2019 to 2023; meanwhile, consumer perceptions and major issues formed by seniors’ participation in leisure activities as well as social For reduced wordiness participation in senior fashion and the process of educating them were identified. Third, as a result of the emotion analysis, it was found that the ratio of positive emotions towards senior fashion for the two periods from 2014 to 2018 and 2019 to 2023 was generally high. Through the analyses, it can be seen that senior fashion is gradually spreading according to leisure and social activities. In conclusion, this study is meaningful in that it confirmed the changes in keywords, trends, and perceptions by using big data to revitalize the senior market, which has great potential among the major target markets of the fashion industry.

영어초록

To understand the flow and issues associated with changes in the social perception of senior fashion through big data analysis, this study first identified important keywords and overall trends related to senior fashion. Second, the use of senior fashion through clusters was investigated, and third, the process of changing emotions towards senior fashion keywords was investigated. Using Textom, big data on senior fashion were collected for two periods: from January 1, 2014 to December 31, 2018 and from January 1, 2019 to December 31, 2023. To analyze the data, text mining techniques, CONCOR analysis, and emotion analysis were conducted. The results of this study are as follows: First, through text mining, we established that the core keywords of senior fashion from 2014 to 2018 were 'senior', 'fashion', 'model', 'fashion show', 'clothes', and 'culture', and those from 2019 to 2023 were 'model', 'senior', 'fashion show', 'class', and 'fashion'. Second, as a result of the CONCOR analysis, five clusters were derived from 2014 to 2018 and four from 2019 to 2023; meanwhile, consumer perceptions and major issues formed by seniors’ participation in leisure activities as well as social For reduced wordiness participation in senior fashion and the process of educating them were identified. Third, as a result of the emotion analysis, it was found that the ratio of positive emotions towards senior fashion for the two periods from 2014 to 2018 and 2019 to 2023 was generally high. Through the analyses, it can be seen that senior fashion is gradually spreading according to leisure and social activities. In conclusion, this study is meaningful in that it confirmed the changes in keywords, trends, and perceptions by using big data to revitalize the senior market, which has great potential among the major target markets of the fashion industry.

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