DOI QR코드

DOI QR Code

Social media comparative analysis based on multidimensional scaling

  • Received : 2014.04.02
  • Accepted : 2014.04.28
  • Published : 2014.05.31

Abstract

As social media draws attention as a business tool, organizations, large or small, are trying to exploit social media in their business. However, lack of understanding the characteristics of each social media led them to develop a naive strategy for dealing with social media. Thus, this study aims to deepen the understanding by comparatively analyzing how social media users perceive (the image of) each social media. Facebook, Twitter, YouTube, Blogs, Communities and Cyworld were chosen for our study and data from 132 respondents were analyzed using multidimensional scaling technique. The results show that there are meaningful differences in users' perception of social media attributes, which are grouped into four; information feature, motivation, promotion tool, usability. It is also analyzed whether such differences can be found between male and female users. (Such differences are also analyzed in both male and female users' perceptions.) Further, we discuss some implications of the research results for both practitioners and researchers.

Keywords

References

  1. Agrawal, D., Budak, C., El Abbadi, A., Georgiou, T. and Yan, X. (2014). Big data in online social networks: User interaction analysis to model user behavior in social networks, Databases in Networked Information Systems, 1-16.
  2. Bae, H. W., Kwon, K. H., Moon, M. N. and Moon, H. S. (2010). Multidimensional scaling analysis on the image of special purpose academies. Journal of Korean Data & Information Science Society, 21, 11-21.
  3. Carroll, J. D. and Arabie, P. (1998). Multidimensional scaling. Measurement, Judgment and Decision Making, 179-250.
  4. Catanese, S. A., De Meo, P., Ferrara, E., Fiumara, G. and Provetti, A. (2011). Crawling facebook for social network analysis purposes. In Proceedings of the International Conference on Web Intelligence, Mining and Semantics, Association for Computing Machinery, 52-59.
  5. Gartner, W. C. (1989). Tourism image: Attribute measurement of state tourism products using multidimensional scaling techniques. Journal of Travel Research, 28, 16-20. https://doi.org/10.1177/004728758902800205
  6. Gillin, P. (2008). Secrets of social media marketing: How to use online conversations and customer communities to turbo-charge your business! Linden Publishing, Fresno.
  7. Green, P. E. and Carmone, F. J. (1970). Multidimensional scaling and related techniques in marketing analysis, Allyn and Bacon, Boston.
  8. Hunt, T. (2009). The Whuffie factor: Using the power of social networks to build your business, Crown Business, New York.
  9. Jung, T., Youn, H. and McClung, S. (2007). Motivations and self-presentation strategies on Korean-based Cyworld weblog format personal homepages. CyberPsychology & Behavior, 10, 24-31. https://doi.org/10.1089/cpb.2006.9996
  10. Kaplan, A. M. and Haenlein M. (2010). Users of the world, unite! The challenges and opportunities of Social Media. Business Horizons, 53, 59-68. https://doi.org/10.1016/j.bushor.2009.09.003
  11. Kim, S., Lee, H., Suh, Y. and Han, J. (2013). Enhancing the corporate image through social media: An approach based on multi-dimensional scaling. Journal of the Korean Data & Information Science Society, 24, 427-436. https://doi.org/10.7465/jkdi.2013.24.3.427
  12. Lee, H. (2013). Data analysis using SPSS, Cheongram, Seoul.
  13. Mangold, W. G. and Faulds, D. J. (2009). Social media: The new hybrid element of the promotion mix. Business Horizons, 52, 357-365. https://doi.org/10.1016/j.bushor.2009.03.002
  14. Mathioudakis, M. and Koudas, N. (2010). Twittermonitor: Trend detection over the twitter stream. In Proceedings of the 2010 ACM SIGMOD International Conference on Management of Data, Association for Computing Machinery, 1155-1158.
  15. Mugavin, M. E. (2008). Multidimensional scaling: A brief overview. Nursing Research, 57, 64-68. https://doi.org/10.1097/01.NNR.0000280659.88760.7c
  16. New York Times. (2009). For many businesses with low ad budget, the social media networking is their sole means of marketing, 23, July.
  17. Raacke, J. and Bonds-Raacke, J. (2008). MySpace and Facebook: Applying the uses and gratifications theory to exploring friend-networking sites. CyberPsychology & Behavior, 11, 169-174. https://doi.org/10.1089/cpb.2007.0056
  18. Ryan, T. and Xenos, S. (2011). Who uses Facebook? An investigation into the relationship between the big five, shyness, narcissism, loneliness, and Facebook usage. Computers in Human Behavior, 27, 1658-1664. https://doi.org/10.1016/j.chb.2011.02.004
  19. Safko, L. and Brake, D. K. (2009). The social media bible: Tactics, tools & strategies for business success, John Wiley & Sons, Hoboken.
  20. Scoble, R. and Israel, S. (2006). Naked conversations, how blogs are changing the way businesses talk with customers, John Wiley and Sons, Hoboken.
  21. Surowiecki, J. (2004). The wisdom of crowds: Why the many are smarter than the few and how collective wisdom shapes business, economies, societies and nations, Doubleday, New York.
  22. Tapscott, D. and Williams, A. (2006). Wikinomics: How mass collaboration changes everything, Portfolio, New York.
  23. Tosun, L. P. (2012). Motives for Facebook use and expressing "true self" on the Internet. Computers in Human Behavior, 28, 1510-1517. https://doi.org/10.1016/j.chb.2012.03.018
  24. Weinberg, B. D. and Pehlivan, E. (2011). Social spending: Managing the social media mix. Business Horizons, 54, 275-282. https://doi.org/10.1016/j.bushor.2011.01.008
  25. Weinberg, T. (2009). The new community rules: Marketing on the social web, O'Reilly Media, Inc., Sebastopol
  26. Wikipedia, Blog. (2011). http://en.wikikpedia.org/wiki/Blog.
  27. Wikipedia, Chris Shipley. (2013). http://en.wikipedia.org/wiki/Chris_Shipley.
  28. Wikipedia, Twitter. (2012). http://en.wikipedia.org/wiki/Twitter.

Cited by

  1. Classification of ratings in online reviews vol.27, pp.4, 2016, https://doi.org/10.7465/jkdi.2016.27.4.845