Browse > Article

Determining Contents Power Users for Revitalizing Blog Networks  

Lim, Seung-Hwan (한양대학교 전자컴퓨터 통신공학과)
Kim, Sang-Wook (한양대학교 전자컴퓨터 통신공학과)
Park, Sun-Ju (연세대학교 경영대학)
Lee, Joon-Ho ((주) NHN)
Publication Information
Journal of KIISE:Databases / v.36, no.6, 2009 , pp. 411-421 More about this Journal
Abstract
In a blog network, there are special users who induce other users to actively utilize blog services. In this paper, these users whose contents exhibit large influence over other bloggers are defined as 'Content Power Users' (CPUs). It is important to accurately determine who content power users are in a blog network in order to establish business policies that will stimulate usage of blog services. In this paper, we discuss a novel method of determining content power users. First, we propose a system of measuring the influence of content of each post owned by individual users. Then, by adjusting the measured values based on the time of exposure and adding them up, we calculate the power of influence for corresponding users. Finally, by applying the proposed method to actual blog networks and comparing the selected power users to those of a preexisting method, we analyze different methods of determining power users. The experimental results demonstrate that our method of determining power users reflects well dynamic changes in a blog network.
Keywords
Social Network Analysis; Content Power User; Blog; Data Mining; Information Diffusion;
Citations & Related Records
연도 인용수 순위
  • Reference
1 S. Wasserman and K. Faust, Social Netuiork Analysis : Methods and Applications, Cambridge University Press, 1994
2 S. Redner, 'How Popular Is Your Paper?,' European Physics Journal B, vol.4, no.2, pp. 131-134, 1998   DOI   ScienceOn
3 M. Granovetter, 'The Strength of Weak Ties,' American Journal of Sociology, vol.78, no.6, pp.1360-1380, 1973   DOI   ScienceOn
4 X. Song et al., 'Mining in Social Networks Information Flow Modeling based on Diffusion Rate for Prediction and Ranking,' In Proc. Int'I. Conf. on World Wide Web, pp.l91-200, 2007   DOI
5 (주)위고넷 이브랜딩 전략연구소, 커뮤니티를 승부하는 브랜드 전략, 이디자인, 2004
6 D. Kempe, J Kleinberg, and E. Tardos, 'Maximizing the Spread of Influence through a Social Network,' In Proc. ACM Int'l. Conf. on Knowledge Discovery and Data Mining, ACM SIGKDD, pp. 137-146, 2003   DOI
7 (주)SK Communications, http://www.cyworld.com
8 (주)아이세이브존, http://www.isavezone.com
9 J Brown and P. Reinegen, 'Social Ties and Word-of-Mouth Referral Behavior,' Journal of Consumer Research, vol.1, no.3, pp.350-362, 1987   DOI   ScienceOn
10 A. Bavelas, 'Communication patterns in taskoriented groups,' Journal of the Acoustical Society of America, 22, pp. 271-282, 1950   DOI
11 C. Proctor and C. Loomis, Analysis of sociometric data, Research Methods in Social Relations, pp. 561-586, 1951
12 J. Coleman, H. Menzel, and E. Katz, Medical Innovations: A Diffusion Study, Bobbs Merrill, 1966
13 S. Milgram, 'The Small World Problem,' Physiology Today, vol.2, pp.60-67, 1967
14 A. Nowak, Virus Dynamics: Mathematical Principles of Immunology and Virology, Oxford Lniversity Press. 2000
15 H. Jeong et aI., 'The Large-Scale Organization of Metabolic Networks,' Nature, vol.407, pp. 651-654, 2000   DOI   ScienceOn
16 J Iribarren and E. Moro, 'Information Diusion Epidemics in Social Networks,' Arxiv, 0706.0641, 2007
17 D. Watts and S. Strogatz, 'Collective Dynamics of 'Small-World' Networks,' Nature, vol.393, pp. 440-442, 1998   DOI   PUBMED   ScienceOn
18 D. Watts, Small Worlds: The Dynamics of Networks Between Order and Randomness, Princeton, New Jersey: Princeton University Press, 1999
19 R. Albert, H. Jeong, and A. Barabasi, 'Diameter of the World Wide Web,' Nature, vo1.401, pp. 130-131, 1999   DOI   ScienceOn
20 (주)NHN, 블로그홈, blog.naver.com
21 A. Shimbel, 'Structural parameters of communication networks,' Bulletin of Mathematical Biophysics, 15, pp.501-507, 1953   DOI
22 (주)엠파스, http://blog.empas.com