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New Technology of Library and Information Service  2013, Vol. 29 Issue (10): 36-42    DOI: 10.11925/infotech.1003-3513.2013.10.07
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Survey on Community Detecting in Social Media
Wu Xiaolan1,2, Zhang Chengzhi1
1. Department of Information Management, Nanjing University of Science and Technology, Nanjing 210094, China;
2. School of Management Science and Engineering, Anhui University of Finance & Economics, Bengbu 233030, China
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Abstract  Social media generally shows the network of users, which contributes to the rapid formation of the user community. The definition of social media communities and its characteristics are analyzed and summarized firstly in this paper, then the main research contents and progress on community detection are introduced from the five categories of social media networks. Finally, it is concluded that existing studies focus on social media community detection algorithm, statistical analysis of social media community structure and temporal analysis of social media communities, and the existing problems and future research directions are pointed out.
Key wordsSocial media      Community detection      Community structure     
Received: 26 July 2013      Published: 04 November 2013
:  G350  

Cite this article:

Wu Xiaolan, Zhang Chengzhi. Survey on Community Detecting in Social Media. New Technology of Library and Information Service, 2013, 29(10): 36-42.

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[1] Newman M E J, Girvan M. Finding and Evaluating Community Structure in Networks[J]. Physical Review E, 2004, 69(2): 026113.
[2] Papadopoulos S, Kompatsiaris Y, Vakali A, et al. Community Detection in Social Media[J]. Data Mining and Knowledge Discovery, 2012, 24(3): 515-554.
[3] Wasserman S,Faust K. Social Network Analysis: Methods and Applications[M]. Cambridge University Press, 1994.
[4] Scott J. Social Network Analysis: A Handbook[M].The 2nd Edition.London:Sage Publications Ltd, 2000.
[5] Borgatti S P, Everett M G, Shirey P R. LS Sets, Lambda Sets and Other Cohesive Subsets[J]. Social Networks, 1990, 12(4): 337-357.
[6] Radicchi F, Castellano C, Cecconi F, et al.Defining and Identifying Communities in Networks[J]. Proceedings of the National Academy of Sciences of the United States of America, 2004, 101(9): 2658-2663.
[7] 张婷娜. 复杂网络模块度的研究[D]. 西安:西安理工大学, 2010. (Zhang Tingna. Analysis about Modularity of Complex Networks[D].Xi'an: Xi'an University of Technology,2010.)
[8] Shi J, Malik J. Normalized Cuts and Image Segmentation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(8): 888-905.
[9] Kannan R, Vempala S, Vetta A. On Clusterings: Good, Bad and Spectral[J]. Journal of the ACM, 2004, 51(3): 497-515.
[10] Palla G, Derényi I, Farkas I, et al. Uncovering the Overlapping Community Structure of Complex Networks in Nature and Society[J]. Nature, 2005, 435(7043): 814-818.
[11] Van Dongen S. Graph Clustering by Flow Simulation[D]. Utrecht, Netherlands:Dutch National Research Institute for Mathematics and Computer Science, 2000.
[12] Arenas A, Díaz-Guilera A, Pérez-Vicente C J. Synchronization Reveals Topological Scales in Complex Networks[J]. Physical Review Letters, 2006, 96(11): 114102.
[13] Raghavan U N, Albert R, Kumara S. Near Linear Time Algorithm to Detect Community Structures in Large-scale Networks[J]. Physical Review E, 2007, 76(3): 036106.
[14] 胡海波, 王科, 徐玲, 等. 基于复杂网络理论的在线社会网络分析[J]. 复杂系统与复杂性科学, 2008, 5(2): 1-14.(Hu Haibo, Wang Ke, Xu Ling, et al. Analysis of Online Social Networks Based on Complex Network Theory[J].Complex Systems and Complexity Science,2008,5(2): 1-14.)
[15] Xu X, Yuruk N, Feng Z, et al. SCAN: A Structural Clustering Algorithm for Networks[C].In:Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2007: 824-833.
[16] Scripps J, Tan P N, Esfahanian A H. Node Roles and Community Structure in Networks [C].In:Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 Workshop on Web Mining and Social Network Analysis. New York, NY, USA:ACM, 2007: 26-35.
[17] 朱天. 社会网络中节点角色以及群体演化研究[D]. 北京:北京邮电大学, 2011. (Zhu Tian.Research on Node Role and Group Evolution in Social Network[D]. Beijing: Beijing University of Posts and Telecommunications,2011.)
[18] Kaplan A M, Haenlein M. Users of the World, Unite! The Challenges and Opportunities of Social Media[J]. Business Horizons, 2010, 53(1): 59-68.
[19] 黄启镖. 在线虚拟社区游戏评估[D]. 北京:北京邮电大学, 2009. (Huang Qibiao.Evaluation of Virtual Community of On-line Game[D]. Beijing: Beijing University of Posts and Telecommunications,2009.)
[20] Kumar R, Novak J, Raghavan P, et al. On the Bursty Evolution of Blogspace[J]. World Wide Web, 2005, 8(2): 159-178.
[21] Tseng B L, Tatemura J, Wu Y. Tomographic Clustering to Visualize Blog Communities as Mountain Views[C]. In:Proceedings of the WWW 2005 Workshop on the Weblogging Ecosystem. 2005.
[22] Lin Y R, Sundaram H, Chi Y, et al. Discovery of Blog Communities Based on Mutual Awareness[C].In: Proceedings of the 3rd Annual Workshop on the Weblogging Ecosystem. 2006.
[23] Chau M, Xu J. Mining Communities and Their Relationships in Blogs: A Study of Online Hate Groups[J]. International Journal of Human-Computer Studies, 2007, 65(1): 57-70.
[24] Lin Y R, Chi Y, Zhu S, et al. Facetnet: A Framework for Analyzing Communities and Their Evolutions in Dynamic Networks[C].In:Proceedings of the 17th International Conference on World Wide Web. New York, NY, USA: ACM, 2008: 685-694.
[25] 柳助民, 李绍滋, 林达真, 等. 基于 PCM 聚类算法的 Blog 社区发现[J]. 厦门大学学报:自然科学版, 2009, 48(4): 508-513.(Liu Zhumin,Li Shaozi, Lin Dazhen, et al. Blog Community Discovery Based on PCM Clustering Algorithm[J]. Journal of Xiamen University: Natural Science,2009, 48(4): 508-513.)
[26] 罗乐. 基于核心成员识别的网络社区发现及跟踪方法[D]. 哈尔滨: 哈尔滨工业大学, 2010.(Luo Le. Community Discovery and Tracking Methods Based on Core Members[D]. Harbin: Harbin Institute of Technology,2010.)
[27] Kleinberg J M. Authoritative Sources in a Hyperlinked Environment[J]. Journal of the ACM, 1999, 46(5): 604-632.
[28] Derényi I, Palla G, Vicsek T. Clique Percolation in Random Networks[J]. Physical Review Letters, 2005, 94(16): 160202.
[29] Java A, Song X, Finin T, et al. Why We Twitter:Understanding Microblogging Usage and Communities[C]. In: Proceedings of the Joint 9th WEBKDD and 1st SNA-KDD Workshop. New York, NY, USA:ACM Press, 2007:56-65.
[30] 袁毅, 杨成明. 微博客用户信息交流过程中形成的不同社会网络及其关系实证研究[J]. 图书情报工作, 2011, 55(12): 31-35.(Yuan Yi, Yang Chengming.Empirical Analysis of All Kinds of Social Networks and Their Relationships Formed by Information Communication among Microblog Users[J]. Library and Information Service,2011, 55(12): 31-35.)
[31] 范超然, 黄曙光, 李永成. 微博社交网络社区发现方法研究[J]. 微型机与应用, 2012, 31(23): 67-70.(Fan Chaoran,Huang Shuguang,Li Yongcheng.Study on Microblog Social Network Community Detection[J]. Microcomputer & Its Application,2012, 31(23): 67-70.)
[32] Zakharov P. Thermodynamic Approach for Community Discovering within the Complex Networks: LiveJournal Study[OL]. arXiv preprint physics/0602063, 2006.
[33] Leskovec J, Lang K J, Dasgupta A, et al. Statistical Properties of Community Structure in Large Social and Information Networks[C].In: Proceedings of the 17th International Conference on World Wide Web. New York, NY, USA: ACM, 2008: 695-704.
[34] Lancichinetti A, Kivel M, Saramki J, et al. Characterizing the Community Structure of Complex Networks[J]. PLoS One, 2010, 5(8): e11976.
[35] 刘耀庭. 社交网络结构研究[D]. 杭州: 浙江大学, 2008.(Liu Yaoting. Research on Social Network Structure[D].Hangzhou: Zhejiang University,2008.)
[36] 窦炳琳, 李澍淞, 张世永. 基于结构的社会网络分析[J]. 计算机学报, 2012, 35(4):741-753.(Dou Binglin,Li Shusong,Zhang Shiyong.Social Network Analysis Based on Structure[J].Chinese Journal of Computers, 2012, 35(4): 741-753.)
[37] Zlatić V, Božiić eviić M, Štefaničiić H, et al. Wikipedias: Collaborative Web-based Encyclopedias as Complex Networks[J]. Physical Review E, 2006, 74(1): 016115.
[38] Capocci A, Servedio V D P, Colaiori F, et al. Preferential Attachment in the Growth of Social Networks: The Internet Encyclopedia Wikipedia[J]. Physical Review E, 2006, 74(3): 036116.
[39] Broder A, Kumar R, Maghoul F, et al. Graph Structure in the Web[J]. Computer Networks, 2000, 33(1-6): 309-320.
[40] Asur S,Parthasarthy S,Ucar D.An Event-based Framework for Characterizing the Evolutionary Behavior of Interaction Graphs[C].In: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining(KDD),San Jose, California,USA. New York, NY, USA:ACM,2007:913-921.
[41] Lizorkin D, Medelyan O, Grineva M. Analysis of Community Structure in Wikipedia[C].In:Proceedings of the 18th International Conference on World Wide Web. New York, NY, USA:ACM, 2009: 1221-1222.
[42] Jesus R, Schwartz M, Lehmann S. Bipartite Networks of Wikipedia's Articles and Authors: A Meso-level Approach[C].In:Proceedings of the 5th International Symposium on Wikis and Open Collaboration. New York, NY, USA:ACM, 2009: 1-10.
[43] 杨方方.面向社会化媒体的社会网络挖掘与分析[D].哈尔滨:哈尔滨工业大学,2011.(Yang Fangfang. Social Network Mining and Analysis Based on Social Media[D]. Harbin:Harbin Institute of Technology,2011.)
[44] Saha B, Getoor L. Group Proximity Measure for Recommending Groups in Online Social Networks[J]. Networks, 2008, 1(6): 5.
[45] Kumar R, Novak J, Tomkins A. Structure and Evolution of Online Social Networks[A].//Link Mining: Models, Algorithms, and Applications[M]. New York: Springer, 2010: 337-357.
[46] Chakraborty A, Ghosh S, Ganguly N. Detecting Overlapping Communities in Folksonomies[C].In:Proceedings of the 23rd ACM Conference on Hypertext and Social Media. New York, NY, USA: ACM, 2012: 213-218.
[47] 燕飞, 张铭, 谭裕韦, 等. 综合社会行动者兴趣和网络拓扑的社区发现方法[J]. 计算机研究与发展, 2010, 47(S1): 357-362.(Yan Fei,Zhang Ming,Tan Yuwei, et al. Community Discovery Based on Actors' Interests and Social Network Structure[J].Journal of Computer Research and Development,2010, 47(S1): 357-362.)
[48] 杨阳.在线社会网络社区发现和社区特征分析[D].北京:北京交通大学, 2011.(Yang Yang. Analysis on Community Detection and Characteristics of Online Social Network[D].Beijing:Beijing Jiaotong University,2011.)
[49] 黄中杰.社交网络中的视频观看质量优化[D].上海:复旦大学,2012.(Huang Zhongjie.Video Playback Quality Optimization in Social Network[D].Shanghai:Fudan University,2012.)
[50] Brignall T W, Van Valey T L. An Online Community as a New Tribalism: The World of Warcraft[C]. In:Proceedings of the 40th Annual Hawaii International Conference on System Sciences(HICSS 2007). IEEE, 2007.
[51] Bainbridge W S. The Warcraft Civilization: Social Science in a Virtual World[M]. London,England:The MIT Press,2010.
[52] Ducheneaut N, Yee N, Nickell E, et al. The Life and Death of Online Gaming Communities: A Look at Guilds in World of Warcraft[C].In:Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2007: 839-848.
[53] Girvan M, Newman M E J. Community Structure in Social and Biological Networks[J]. Proceedings of the National Academy of Sciences, 2002, 99(12): 7821-7826.
[54] Von Luxburg U. A Tutorial on Spectral Clustering[J]. Statistics and Computing, 2007, 17(4): 395-416.
[55] 叶祺. 大规模网络的社团发现与多层次可视化分析[D]. 北京:北京邮电大学, 2011.(Ye Qi. Community Detection and Multi-level Visual Analytics for Massive Networks[D]. Beijing: Beijing University of Posts and Telecommunications,2011.)
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