Advanced SearchSearch Tips
Analysis of Outdoor Wear Consumer Characteristics and Leading Outdoor Wear Brands Using SNS Social Big Data
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
  • Journal title : Fashion & Textile Research Journal
  • Volume 18, Issue 1,  2016, pp.48-62
  • Publisher : The Society of Fashion and Textile Industry
  • DOI : 10.5805/SFTI.2016.18.1.48
 Title & Authors
Analysis of Outdoor Wear Consumer Characteristics and Leading Outdoor Wear Brands Using SNS Social Big Data
Jung, Hye Jung; Oh, Kyung Wha;
  PDF(new window)
Consumers have come to demand high quality, affordable prices, and innovative product designs of the outdoor wear market due to their well-being and leisure oriented lifestyle. A new system of business in outdoor wear has emerged in the process through which corporations have endeavored to satisfy such consumer needs. Outdoor wear brands have utilized social network services (SNS) such as Facebook and Twitter as means of marketing and have built close relations with consumers based on communication through these media. Recently, explosively escalating SNS data are referred to as social big data, and now that every consumer online is a commentator, reviewer, and publisher, the outdoor wear market and all of its brands have to stop talking and start listening to how they are perceived. Therefore, this study employs Social , a social big data analysis solution by Daumsoft, Inc., to verify changes in the allusions related to outdoor wear market found on SNS. This study aims to identify changes in consumer perceptions of outdoor wear based on changes in outdoor wear search words and trends in positive and negative public opinion found in SNS social big data. In addition, products of interest, the major brands mentioned, the attributes taken into consideration during purchases of products, and consumers` psychology were categorized and analyzed by means of keywords related to outdoor wear brands found on SNS. The results of this study will provide fundamental resources for outdoor wear brands` market entry and brand strategy implementation in the future.
outdoor wear;consumer analysis;brand analysis;social network service;social big data;
 Cited by
'2014 outdoor survey-Significantly increased young people go to mountains'. (2014, January 14). Mountain. Retrieved August 18, 2015, from

Bae, J. H., Son, J. E., & Song, M. (2013). Analysis of twitter for 2012 South Korea presidential election by text mining techniques. Journal of Intelligence and Information Systems, 19(3), 141-156.. doi:10.13088/jiis.2013.19.3.141

Beyer, M. A., & Laney, D. (2012). The importance of 'big data': A definition. Stamford, CT: Gartner. Retrieved June 22, 2014, from

Breuer, P., Forina, L., & Moulton, J. (2013). Beyond the hype: Capturing value from big data and advanced analytics. McKinsey and Company. Retrieved June 20, 2014, from

Cho, S., & Workman, J. E. (2015). College students' frequency of use of information sources by fashion leadership and style of information processing. Fashion and Textiles, 2(1), 1-18. doi:10.1186/s40691-015-0049-2 crossref(new window)

Choi, J. H., Choi, D. H., Kim, D. H., Kim, S. S., Lim, S. R., & Kang, J. W. (2014). 소셜 빅데이터를 활용한 의사 결정 검색 기술 [Decision-making search technology utilizing social big data]. Korean Institute of Information Scientists and Engineers, 32(1), 44-52.

Chung, T. R., Hwang, H. Y., Lim, B. K., & Lee, D. Y. (2012). A study on relationships among the purchase decision factors, brand images, intent for word of mouth and repurchase intention of teenagers for outdoor brand apparels. The Korean Journal of Physical Education, 51(3), 183-192.

Fashionbiz. (2015, July 28). 아웃도어, '아쿠아슈즈' 각축전 화끈 [Outdoor, keen competition of 'aqua shoes' between brands]. Retrieved February 11, 2016 from

Gantz, J., & Reinsel, D. (2011). Extracting value from chaos. IDC Review, 1-12. Retrieved June 23, 2015, from

Global Fashion Forum. (2014, September 18). 패션, 빅데이터를 만나다. [Fashion meets big data], 패션업계의 빅데이터 활용 [Utilizing big data in fashion industry]. Fashionnetkorea. Ministry of Trade, Industry & Energy, Korea, pp. 76-159.

Hong, B. S., Kim, C. H., & Lee, E. J. (2010). The effect of self-efficacy and commitment on functional satisfaction and repurchase intention of mountaineering apparels. Fashion & Textile Research Journal, 12(5), 599-607. crossref(new window)

Hutton, G., & Fosdick, M. (2011). The globalization of social media: Consumer relationships with brands evolve in the digital space. Journal of Advertising Research, 51(4), 564-570. doi:10.2501/JAR-51-4-564-570 crossref(new window)

Jang, W. Y., Lee, K. Y., & Won, D. Y. (2015). The market segmentation through purchasing decision factors of outdoor sports, wear using conjoint analysis. Korean Journal of Sport Management, 20(3), 117-130.

Je, E. S. (2012). Study on the clothing selection criteria and purchasing satisfaction according to the outdoor wear benefit. Journal of Fashion Business, 16(4), 1-12. doi:10.12940/jfb.2012.16.4.001

Jho, W. S., & Kim, J. Y. (2012). Political communication and civic participation through blogs and twitter. Journal of Cybercommunication Academic Studies, 29(2), 95-130.

Jung, M., Rho, H., & Park, M. (2014). Reaction survey of tourist who railway utilizing SNS bit data. Proceedings of 2014 Korea Railway Association, Fall Conference, Korea, pp. 456-461.

Kim, H. C., Kim, M. J., & Shin, H. J. (2014a). Method for analysis of social data service design and implementation of Jeju tourism trends. The e-Business Studies, 15(3), 173-195.

Kim, H., Ahn, S. K., & Forney, J. A. (2014b). Shifting paradigms for fashion: From total to global to smart consumer experience. Fashion and Textiles, 1(1), 1-16. doi:10.1186/s40691-014-0015-4 crossref(new window)

Kim, T. W., Jung, W. J., & Lee, S. Y. (2014c). The analysis on the relationship between firms' exposures to SNS and stock prices in Korea. Asia Pacific Journal of Information Systems, 24(2), 233-253. crossref(new window)

Kim, I. H., & Ha, J. S. (2012). A study on design characteristics in outdoor wear. Journal of the Korean Society of Fashion Design, 12(1), 93-109.

Kim, J. K., Kim, B. H., & Kang, H. M. (2010). A study on positioning strategy of outdoor sportswear brand based on selected attributes evaluation. Korean Journal of Sport Management, 15(4), 13-24.

Kim, K. H., & Oh, S. R. (2009). Methodology for applying text mining techniques to analyzing online customer reviews for market segmentation. Journal of Korean Contents Association, 9(8), 272-284. crossref(new window)

Kim, S. W., & Kim, N. G. (2014). A study on the effect of using sentiment lexicon in opinion classification. Journal of Intelligence and Information Systems, 20(1), 133-148. doi:10.13088/jiis.2014.20.1.133

Kim, S. H,, Hwang, S. Y, & Kim, Y. I. (2007). A study of differences between lifestyle types in motivation and the effect of motivation on satisfaction of participants in leisure sports activities. Korean Journal of Hotel Administration, 16(2), 35-50.

Kim, T. H. (2009, June 22). 아웃도어 시장의 현황과 전망 [The prospects of outdoor markets]. Kis Credit Monitor. Retrieved August 29, 2014, from

Kim, Y. H., Oh, K. W., & Jung, H. J. (2015). Determinants of ecofriendly outdoor wear products purchase intention: Exploring value-belief-norm theory. Fashion & Textile Research Journal, 17(6), 965-977. doi:10.5805/SFTI.2015.17.6.965 crossref(new window)

Korea Fashion & Textile News. (2015, December 15). 아웃도어 '방한 부츠' 판매전 [Outdoor winter warm boots' sales strategy]. Retrieved February 11, 2016, from

Korea Federation of Textile Industries. (2013). Textile & fashion trend report. Retrieved August 17, 2015, from

Lee, J. H. (2012). 데이터 빅뱅, 빅데이터의 동향 [Data big bang, trends in Big Data]. Journal of Communications & Radio Spectrum, 47(3), 43-55.

Lee, S. K. (2015). A review of big data analysis based on marketing perspective. Korean Journal of Business Administration, 28(1), 21-35.

Lee, S. H., & Yi, Y. J. (2013). Gift for myself: A qualitative study of self-gift behavior in Korea. Consumer Studies, 24(3), 123-155.

Lee, Y. J., & Yoon, J. H. (2014). A study on utilizing SNS big data in the tourism studies : Based on an analysis of key words for tourism information search. International Journal of Tourism and Hospitality Research, 28(3), 5-14.

Lee, Y. J., Seo, J. H., & Choi, J. T. (2014). Fashion trend marketing prediction analysis based on opinion mining applying SNS text contents. Journal of Korean Instituted of Information Technology, 12(12), 163-170. doi:10.14801/jkiit.2014.12.12.163

Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. H. (2011). Big data: The next frontier for innovation, competition and productivity. New York: McKinsey & Company.

Ministry of Culture, Sports and Tourism. (2008). National Survey of Leisure Activities. Retrieved August 24, 2014, from

Paek, K. J., & Lee, J. R. (2014). Draft proposal of smart outdoor wear upon the outdoor wear functionality demand. Fashion & Textile Research Journal, 16(3), 446-455. doi:10.5805/SFTI.2014.16.3.446 crossref(new window)

Park, J. Y., Lee, T. W., Jang, C. R., & Hong, T. H. (2012). 소셜네트워크에서의 관계추천을 위한 데이터 마이닝. [Data mining for relationship recommendation on social network]. Proceeding of the Korea Society of Management Information Systems, Spring Conference, Korea, pp. 508-512.

Park, K. M., Park, H. K., Kim, H. G., & Ko, H. D. (2011). SNS에서 오피니언마이닝 연구 [Opinion mining research in SNS]. Communications of the Korean Institute of Information Scientists and Engineers, 29(11), 54-60.

Park, J. H. (2014). 아웃도어 섬유소재 및 용품: 아웃도어 스포츠 의류시장의 현황과 전망 [Outdoor fiber materials and supplies: Status and prospect of outdoor sports clothing market]. Fiber Technology and Industry, 18(2), 91-95.

Rhee, Y. J., & Lee, E. O. (2011). The qualitative study on outdoor sportswear purchase behavior-Focusing on functional fabric awareness level and benefits sought-. The Research Journal of the Costume Culture, 19(5), 1088-1101. crossref(new window)

Seo, H. J. (2015). A study of outdoor wear consumers' behavior model. Unpublished doctoral dissertation, Ewah Womans University, Seoul.

Song, G. Y. (2014a). Building inter-category brand map via social data mining. Unpublished doctoral dissertation, Korea University, Seoul.

Song, T. M. (2014b). Trend analysis health and welfare policy on social big data. Yonsei Medical Journal, 55(1), 254-263. crossref(new window)

Song, T. M., Song J. Y., & Jin, D. L. (2014). Risk prediction of internet addiction disorder by using social big data. Health and Social Welfare Review, 24(3), 106-134. doi:10.15709/hswr.2014.34.3.106

Tehrani, A. F., & Ahrens, D. (2016). Improved forecasting and purchasing of fashion products based on the use of big data techniques. Supply Management Research, 293-312. doi:10.1007/978-3-658-08809-5_1 crossref(new window)

The Korea Agency of Camping & Outdoor Industry. (2015). 캠핑브랜드 인지도 조사 결과 C-BPS(15년1분기) [Camping brand awareness research results C-BPS in the first quarter of 2015]. Retrieved January 23, 2016, from

Yoo, K. H., & Yu, C. H. (2013). A study on the application method of cadastral information big data. Journal of the Korean Cadastre Information Association, 15(2), 31-51.

Yune, H. J., Kim, H. J., & Chang, J. Y. (2010). An efficient search method of product reviews using opinion mining techniques. Journal of KIISE : Computing Practices and Letters, 16(2), 222-226.