09 在线社交网络群体发现研究进展.pdfVIP

第39 卷第9 期 电 子 与 信 息 学 报 Vol.39No.9 2017 年9 月 Journal of Electronics Information Technology Sept. 2017 在线社交网络群体发现研究进展 潘 理* 吴 鹏 黄丹华 (上海交通大学电子信息与电气工程学院 上海 200240) (信息内容分析技术国家工程实验室 上海 200240) 摘 要：群体是在线社交网络重要的中观组织。群体发现不仅有重要的理论意义，还推动了在线社交网络的应用与 发展，有广泛的应用前景。该文总结论述了在线社交网络群体发现的研究进展。在分析群体形成机理的基础上定义 在线社交网络群体，并介绍群体发现问题。根据挖掘群体时采用的不同特征，该文分别阐述基于个体属性特征的群 体发现方法和综合属性与结构特征的群体发现方法。随后从特征选取和检测算法两个方面重点介绍了恶意行为群体 的发现方法。最后，对群体发现进一步的研究方向进行展望。 关键词：在线社交网络；群体发现；恶意行为群体 中图分类号：TP393 文献标识码：A 文章编号：1009-5896(2017)09-2097-11 DOI: 10.11999/JEIT161192 Reviews on Group Detection in Online Social Networks PAN Li WU Peng HUANG Danhua (School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China) (National Engineering Laboratory for Information Content Analysis Technology , Shanghai 200240, China) Abstract: Groups are important mesoscopic organizations of Online Social Networks (OSNs). Group detection not only has important theoretical significance, but also has a wide range of applications. It promotes the application and development of online social networks. In this paper, group detection technology in online social networks is studied. Based on analyzing the formation mechanism of social groups, the online social network groups is defined and the group detection problem is introduced. According to different features adopted by group detection methods, the methods based on the attribute features only and those based on combination of attribute features and structure features are analyzed, respectively. Especially, it reviews the malici