Browse > Article
http://dx.doi.org/10.9708/jksci.2020.25.10.255

Mobile Commerce Brand Identity Strategy by SNS Text mining  

Yeo, Hyun-Jin (International College, Dongseo University)
Publication Information
Journal of the Korea Society of Computer and Information / v.25, no.10, 2020 , pp. 255-260 More about this Journal
Abstract
In this paper, I propose an efficient brand identity strategy by topic modeling the Instagram posts, one of SNS(Social Network Service) having more than 1billion world-wide and 500 million daily users. Since the 92% age groups of the Instagram is 18~50 years old (59% 18~29y and 33% 30~49), I set research analysis target three mobile commerce sites to dress and cosmetics sales sites that sale apparels cosmetics and gadgets that recently opened and have operated marketing on diverse channel including SNS. By topic modeling SNS posts for 6 months after launching the site that tagged each m-commerce site brand name or company name, I validate companies' brand identity strategy works effectively and suggest moderation of strategy for brand image. As a result, I found one of three mobile commerce site has different brand image by users and need different identity set up.
Keywords
Topic modeling; SNS; Text-mining; Brand Identity; M-Commerce;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 Korea Ministry of Statistics, "2020. JULY Online Shopping Trend", 2020.
2 SG Hong, KH Lee, and HJ Lee, "A Study on trend of brand identity desin-from 2009 to 2018-", The Treatise on The Plastic Media, Vol.21, No.4, pp. 293-303, 2018
3 Alina Wheeler, "Designing Brand Identity: An Essential Guide for the Whole Branding Team", John Wiley & Sons, 2017
4 Chernatony, L., "Brand Management Through Narrowing the Gap Between Brand Identity and Brand Reputation", Journal of Marketing Management, Vol.15, No.1-3, pp. 157-179, 1999   DOI
5 Ghodeswar, B.M., "Building brand identity in competitive markets: a conceptual model", Journal of Product & Brand Management, Vol.17, No.1, pp.4-12, 2008   DOI
6 Obar, Jonathan A. and Wildman, Steve, "Social media definition and the governance challenge: An introduction to the special issue". Telecommunications Policy. Vol.39, No.9, pp.745-750, 2015   DOI
7 Boyd, Danah M. and Ellison, Nicole B, "Social Network Sites: Definition, History, and Scholarship". Journal of Computer-Mediated Communication, Vol.13, No.1, pp.210-230, 2007   DOI
8 Neumeier, Marty, "The Dictionary of Brand", New York City: AIGA Center for Brand Experience, p.20, 2004
9 D. Newman, J. H. Lau, K. Grieser, and T. Baldwin, T, "Automatic evaluation of topic coherence", In Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pp.100-108, 2010.
10 A.Gupta, P.Madan and S.Gupta, "Factors influencing B2C M-commerce Satisfaction and Trust toward M-commerce Service Providers", Journal of Pure and Applied Science & Technology, Vol.2, No.1, pp.59-65, 2011
11 Dobni, D. and Zinkhan, G.M., "In search of brand image: A foundation analysis," Advances in Consumer Research, Vol.17, No.1, pp. 110-119, 1990
12 Peppard, J., "Customer relationship management (CRM) in financial services", European Management Journal, Vol.18 No.3, pp. 312-327, 2000   DOI
13 Padgett, D. and Allen, D., "Communicating experiences: A narrative approach to creating service brand image," Journal of Advertising, Vol.26, No.4, pp.49-62, 1997   DOI
14 YS Hwang et al, "Journalism in Data era", Communication Books, 2017
15 TJ Kim, "Journal news analysis about COVID19 by news bigdata", Korea journal of contents, Vol.20, No.5, pp.457-466, 2020
16 Ashok Srivastava and Mehran Sahami, "Text Mining: Classification, clustering, and application", CRC press, pp.71-89, 2009.
17 D. M. Blei, "Probabilistic topic models", Communications of the ACM, Vol.55, No.4, pp.77-84, 2012.   DOI