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基于拓扑势的重叠社区及社区间结构洞识别——兼论结构洞理论视角下网络的脆弱性

李泓波1, 张健沛2, 杨静2, 白劲波3,4, 初妍2   

  1. 1. 肇庆学院计算机学院, 广东肇庆 526061;
    2. 哈尔滨工程大学计算机科学与技术学院, 黑龙江哈尔滨 150001;
    3. 哈尔滨工程大学经济管理学院, 黑龙江哈尔滨 150001;
    4. 黑龙江工程学院计算机科学与技术学院, 黑龙江哈尔滨 150050
  • 收稿日期:2012-01-29 修回日期:2013-08-28 出版日期:2014-01-25 发布日期:2014-01-25
  • 通讯作者: 张健沛
  • 作者简介:李泓波 男,1971年生,黑龙江人,工学博士.主要研究方向为社会网络、复杂网络上的社区发现、挖掘和分析,以及群体智能和数据挖掘等. E-mail:islhb@126.com
  • 基金资助:
    国家自然科学基金(No.61073041,No.61073043);黑龙江省自然科学基金(No.F200901,No.F200917);黑龙江省教育厅科学技术研究基金(No.12531529);哈尔滨市优秀学科带头人基金(No.2010RFXXG002,No.2011RFXXG015);高等学校博士学科点专项科研基金(No.20112304110011)

Identification of Overlapping Communities and Structural Holes Between Communities Based on Topological Potential—Also on the Fragility of Network from the Perspective of the Structural Hole Theory

LI Hong-bo1, ZHANG Jian-pei2, YANG Jing2, BAI Jin-bo3,4, CHU Yan2   

  1. 1. School of Computer Science, Zhaoqing University, Zhaoqing, Guangdong 526061, China;
    2. College of Computer Science and Technology, Harbin Engineering University, Harbin, Heilongjiang 150001, China;
    3. School of Economics and Management, Harbin Engineering University, Harbin, Heilongjiang 150001, China;
    4. School of Computer Science and Technology, Heilongjiang Institute of Technology, Harbin, Heilongjiang 150050, China
  • Received:2012-01-29 Revised:2013-08-28 Online:2014-01-25 Published:2014-01-25

摘要: 社会网络和复杂网络上的社区识别已经成为当前研究的热点和前沿课题.针对目前社区识别方法不能兼具较低时间复杂度、无须专家知识或先验知识和允许存在重叠节点的不足,提出了基于拓扑势理论的重叠社区识别方法.通过提出的重叠节点社区归属不确定性测度,该方法同时实现了社区间结构洞的识别.实验验证了该方法的有效性.另外,文章在理论证明的基础上提出了影响因子优化算法;论证了结构洞理论视角下网络的脆弱性.

关键词: 网络, 重叠社区, 结构洞, 识别, 拓扑势, 影响因子, 不确定性测度, 脆弱性

Abstract: Community identification has been a hot spot and a cutting-edge topic among researchers.Since none of the present community identification methods simultaneously meets the requirements,such as lower time complexity,independence of expertise or experiences,allowance for overlapping nodes and so on,an overlapping community identification method is proposed based on topological potential theory.This method can also identify the structural holes in communities at the same time by the presented uncertainty measure of the community identity of the overlapping nodes,and its effectiveness is verified by experiments.In addition,an influence factor optimization algorithm is proposed and network fragility is discussed and prooved from the perspective of structural hole theory.

Key words: network, overlapping community, structural holes, identification, topological potential, influence factor, uncertainty measure, fragility

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