References
- Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 3, 993-1022.
- Cho, H. A., & Kim, Y. I. (2020). Characteristics of internet-meme worthy fashion design. Journal of Fashion Design, 20(2), 87-102. doi:10.18652/2020.20.2.6
- Chung, S. J., & Yim, E. H. (2020). Fashion activism in social media: Deconstructing the ideal beauty. Journal of Fashion Design, 20(2), 55-72. doi:10.18652/2020.20.2.4
- Dholakia, R. R., Zhao, M., Dholakia, N., & Fortin, D. R. (2000). Interactivity and revisits to websites: A theoretical framework. RITIM Working Paper, Retrieved from https://www.academia.edu/15042791/Interactivity_and_revisits_to_websites_a_theoretical_framework
- Heeter, C. (1989). Implications of new interactive technologies for conceptualizing communication. In J. L. Salvaggio & J. Bryant (Eds.), Media use in the information age: Emerging patterns of adoption and consumer use, 217-235. Hillsdale, NJ: Lawrence Erlbaum Associates.
- Ho, B. (2022, December 28). Subversive basics: Flaunt wardrobe staples with a rebellious twist. Vogue. Retrieved July 29, 2023, from https://vogue.sg/subversive-basics-style/
- Kim, G. A., & Kim, C. K. (2017). Sentimental analysis to product design using big-data: Focused on smartphone. The Korean Society of Science & Art, 27, 31-48. doi:10.17548/ksaf.2017.01.27.31
- Kim, G. H. (2022). A Study on the characteristics of Amekaji fashion trends using big data text mining analysis. Journal of Fashion Business, 26(3). 138-154. doi:10.12940/jfb.2022.26.3.138
- Kim, H. S. (2017). An exploratory study on the semantic network analysis of food tourism through the big data. Culinary Science & Hospitality Research, 23(4), 22-32. doi:10.20878/cshr.2017.23.4.003
- Kim, J. H., Na, J. Y., & Song, J. W. (2018). Features of science classes in science core schools identified through semantic network analysis. Journal of the Korean Association for Research in Science Education, 38(4), 565-574. doi:10.14697/jkase.2018.38.4.565
- Kim, Y. (2020). 소셜네트워크분석 기법의 이해와 적용: 네트워크 구조와 클러스터링 그리고 QAP [Understanding and application of social network analysis techniques: Network structure, clustering, and QAP]. Korea Institute of Public Administration, 34, 58-68.
- Kim, Y. H., & Kim, Y. J. (2016). 사회연결망 분석 (제4판) [Social network analysis (vol. 4)] Seoul: Pakyoungsa.
- Lee, J. (2020). A study on types of short-form video contents. Humanities Contents, (58), 121-139. doi:10.18658/humancon.2020.09.121
- Lee, J. H., Lee, J. M., & Jang, Y. S. (2017). Analysis of 2018 Pyeongchang olympic keywords using social network big data analysis. Korean Journal of Sport Management, 22(6), 73-89. doi:10.31308/KSSM.22.6.5
- Lee, J., Yun, H. J., & Yun, H. Y. (2022). A study on the characteristics of re-organized shortform contents. Journal of the Korea Contents Association, 22(5), 67-80. doi:10.5392/JKCA.2022.22.05.067
- Lee, S. (2012). 네트워크 분석 방법론 [Network analysis method]. Seoul: Nonhyeong.
- Lee, S. (August 21, 2022). The subversive basics trend is about rebellion. L'officiel, Retrieved July 29, 2023, from https://www.lofficielusa.com/fashion/what-is-subversive-basics-trend-tiktok-runway-y2k-cutouts
- Lee, S. J., & Kim, H. J. (2009). Keyword extraction from news corpus using modified TF-IDF. The Journal of Society for E-business Studies, 14(4), 59-73.
- Lee, W. S. (2021, August 2). '짧고, 강한' 콘텐츠가 통한 다 ['Short, strong' content works]. Insight Korea. Retrieved July 27, 2023, from http://www.insightkorea.co.kr/news/articleView.html?idxno=90641
- Nahm, C. H. (2016). An illustrative application of topic modeling method to a farmer's diary. Cross-Cultural Studies, 22(1), 89-135.
- Orange. (n.d.). Orange. Retrieved Jun 18, 2023, from https://orangedatamining.com/
- Park, C. S. & Chung, C. W. (2013). Text network analysis: Detecting shared meaning through socio-cognitive networks of policy stakeholders. Journal of Governmental Studies, 19(2), 73-108.
- Park, J. H., & Oh, H. J. (2017). Comparison of topic modeling methods for analyzing research trends of archives management in Korea: Focused on LDA and HDP. Journal of Korean Library and Information Science Society, 48(4), 235-258. doi:10.16981/kliss.48.4.201712.235
- Poggi, M. (2022, March 2). How subversive basics became TikTok's favorite fashion hack. Paper. Retrieved June 29, 2023, from https://www.papermag.com/subversive-basics-tiktok-trend-2656824276.html
- Rafaeli, S. (1988). Interactivity from new media to communication. In R. P. Hawkins, J. M. Wiemann, & S. Pingree (Eds.), Advancing Communication Science: Merging Mass and Interpersonal Processes, 110-134. Beverly Hills, CA: Sage.
- Shim, H. R., Choi, M. Y., & Lee, Y. J. (2018). Influence of perceived social distance of SNS visual information on consumers' fashion style preferences. Journal of the Korean Society of Clothing and Textiles, 42(2). 327-341. doi:10.5850/JKSCT.2018.42.2.327
- Subversion. (n.d.). Cambridge Dictionary. Retrieved from July 10, 2023, from https://dictionary.cambridge.org/ko/%EC%82%AC%EC%A0%84/%EC%98%81%EC%96%B4/subversion?q=Subversion
- Text mining. (n.d.). IBM. Retrieved August 15, 2023, from https://www.ibm.com/topics/text-mining
- Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge: Cambridge University Press.
- Yang, H. C., & Cho, H. Y. (2022). Topic modeling analysis of HMR research trends using LDA. Korea Logistics Review, 32(1), 81-92. doi:10.17825/klr.2022.32.1.81
- Zhang, X. F., & Sung, K. S. (2022). An analysis of retro futurism fashion images using social media big data analysis. Design Research, 7(3), 213-223. doi:10.46248/kidrs.2022.3.213