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http://dx.doi.org/10.5850/JKSCT.2022.46.6.1004

Analysis of Global Media Reporting Trends for K-fashion -Applying Dynamic Topic Modeling-  

Hyosun An (Dept. of Fashion Industry, Ewha Womans University)
Jiyoung Kim (Dept. of Clothing and Textiles, Chungbuk National University)
Publication Information
Journal of the Korean Society of Clothing and Textiles / v.46, no.6, 2022 , pp. 1004-1022 More about this Journal
Abstract
This study seeks to investigate K-fashion's external image by examining the trends in global media reporting. It applies Dynamic Topic Modeling (DTM), which captures the evolution of topics in a sequentially organized corpus of documents, and consists of text preprocessing, the determination of the number of topics, and a timeseries analysis of the probability distribution of words within topics. The data set comprised 551 online media articles on 'Korean fashion' or 'K-fashion' published on Google News between 2010 and 2021. The analysis identifies seven topics: 'brand look and style,' 'lifestyle,' 'traditional style,' 'Seoul Fashion Week (SFW) event,' 'model size,' 'K-pop,' and 'fashion market,' as well as annual topic proportion trends. It also explores annual word changes within the topic and indicates increasing and decreasing word patterns. In most topics, the probability distribution of the word 'brand' is confirmed to be on the increase, while 'digital,' 'platform,' and 'virtual' have been newly created in the 'SFW event' topic. Moreover, this study confirms the transition of each K-fashion topic over the past 12 years, along with various factors related to Hallyu content, traditional culture, government support, and digital technology innovation.
Keywords
K-fashion; Text mining; Dynamic Topic Modeling (DTM); Global media; Reporting trends;
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