| 摘要(英) |
In this thesis, we propose a system for finding friend groups in Blogosphere. This system includes two parts: The first part can traverse the Blogosphere so as to obtain the friend network; and the second part is used to find friend groups from the friend network. Our practical performance was tested on Wretch, which is the largest Blogosphere in Taiwan. In today's blog service environment, the establishments of friend relationships are usually unidirectional, i.e., a blogger can add any other as his friend without confirmation. Traditional methods such as clique/club or 2-clique/club are not suitable because the bidirectional link is built incompletely in the social network under such circumstances. To solve this problem, we propose the 1.5-club based on transitive extension. We further make a comparison among the results of finding groups by 1-club, 1.5-club, 2-club and k-clique, and analyze the historical data of social networks from over almost one year. The experimental results show that our proposed method is effective and promising. |
| 參考文獻 |
[1] Dave Sifry, 1999, Blogosphere【Internet】, Available: http://en.wikipedia.org/wiki/Blogosphere【2008/6/11】
[2] Mr. Wednesday, Web上的人際網路 - 從無名小站人際關係分析器WARM談起【Internet】, 2007/2/15,來源: http://mmdays.com/2007/02/15/web-social-network-warm/【2007/2/15】
[3] 游婷喻，2005，部落熱樂陶陶2005持續發燒【Internet】，來源: http://www.insightxplorer.com/news/news_09_13_05.html【2005/9/13】
[4] John Guare, 1990, Six degrees of separation【Internet】, Available: http://en.wikipedia.org/wiki/Six_degrees_of_separation【2008/6/12】
[5] R. Hanneman and M. Riddle, 2005, Introduction to social network methods【Internet】, http://faculty.ucr.edu/~hanneman/networks/nettext.pdf
[6] 許無寒、許\迺赫、吳邦一，Web 2.0時代人際網路之計算問題--以WARM網站為例，第24屆組合數學與計算理論研討會（pp.367-370），國立暨南國際大學，2007
[7] 許無寒、許\迺赫、吳邦一，部落格關聯之擷取與應用--以無名小站之好友連接為例，2007資通技術管理與應用會議（pp.41-45），樹德科技大學，2007
[8] 吳雅樂、陳慧汶、呂妮霖，「無名小站」成為「有名大站」之網站經營者的公關研究-從溝通策略談起，第十五屆廣告暨公共關係國際學術與實務研討會（pp.77-109），國立政治大學，2007
[9] 黃桂貞，如果它當機，三百萬人以上隨即黯然銷魂－七年級生創意無名小站頂起一片天如果它當機，三百萬人以上隨即黯然銷魂－七年級生創意無名小站頂起一片天，交大家族俱樂部四十九期（pp.1-4），2007
[10] J. Han, M. Kamber, 2006, Data Mining: Concepts and Techniques Second Edition, Morgan Kaufmann Publishers Inc.
[11] Wasserman, S. and K. Faust, 1994, Social Network Analysis: Methods and Applications. Cambridge University Press.
[12] 劉江釗，部落格之社會網絡與自我呈現初探，國立中山大學資訊管理學系研究所碩士論文，2004
[13] M. Chau, J. Xu, 2007, Mining Communities and their relationships in blog: A study of online hate groups, International Journal of Human-Computer Studies, 65(1):57-70, January 2007.
[14] Q.-M. Li, M.-W. Xu, J. Hou, and F.-Y. Liu. Web classification based on latent semantic indexing. Journal of Communication and Computer, 3(1):24–27, 2006.
[15] D. Shen, J.-T. Sun, Q. Yang, and Z. Chen. Latent friend mining from blog data. In Proceedings of the Sixth International Conference on Data Mining, pages 552–561, 2006.
[16] M. Morzy. New Algorithms for Mining the Reputation of Participants of Online Auctions. In The 1st Workshop on Internet and Network Economics, pages 112–115, 2005.
[17] P. D. Hoff, A. E. Raftery, and M. S. Handcock. Latent space approaches to social network analysis. Journal of the American Statistical Association, 97(460):1090–1098, December 2002.
[18] D. Liben-Nowell , J. Kleinberg, The link prediction problem for social networks, In International Conference on Information and Knowledge Management(CIKM), pp.556–559, November 2003.
[19] L. Getoor and C. P. Diehl. Link mining: A survey. SIGKDD Explorations, 2(7), pp.3–12, 2005
[20] M. Girvan, M.E.J. Newman, Community structure in social and biological networks, Proceedings of the National Academy of Sciences of the United States of America, pp.7821–7826, 2002.
[21] S. E. Schaeffer. Graph clustering. Computer Science Review, 1(1):27–64, 2007.
[22] Y DONG, Y ZHUANG, KEN CHEN, X TAI, A hierarchical clustering algorithm based on fuzzy graph connectedness, Fuzzy sets and systems, Volume 157, Issue 13, Pages 1760–1774, 1 July 2006 |
