An approach for community detection in social networks based on cooperative games theory

Zhou Lihua; Lü Kevin; Liu Weiyi

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An approach for community detection in social networks based on cooperative games theory

机译：基于合作博弈的社交网络社区发现方法

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摘要

Detecting communities is of great importance in social network analysis. However it is an issue that has not yet been satisfactorily solved, despite the efforts made by interdisciplinary research communities over the past few years, because of the nature of complexity in deciding how community structures should be recognized. In this paper we propose an approach based on cooperative game theory for community detection in social networks. We regard individuals as players, and regard communities as coalitions formed by players, and model community detection problem as the formation and optimization of coalitions. Furthermore, we define coalition profile for players to indicate coalitions that players joined, the order of a coalition profile is defined as the number of coalitions in a coalition profile, and we introduce a utility function to measure preference of coalition profiles. Accordingly, we propose an algorithm to detect a coalition profile with maximal utility function values. We have implemented the algorithms developed in this study and experimental results demonstrate the effectiveness of our approaches.

机译：检测社区在社交网络分析中非常重要。但是，尽管跨学科研究社区在过去几年中做出了努力，但由于决定决定如何识别社区结构的复杂性，该问题尚未得到令人满意的解决。在本文中，我们提出了一种基于合作博弈理论的社交网络社区检测方法。我们将个人视为参与者，将社区视为由参与者组成的联盟，并将社区检测问题建模为联盟的形成和优化。此外，我们为玩家定义了联盟配置文件以指示玩家加入的联盟，联盟配置文件的顺序定义为联盟配置文件中联盟的数量，并且我们引入了效用函数来衡量联盟配置文件的偏好。因此，我们提出了一种算法，用于检测具有最大效用函数值的联合配置文件。我们已经实施了这项研究中开发的算法，实验结果证明了我们方法的有效性。

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来源
《Expert Systems》 |2016年第2期|176-188|共13页
作者
Zhou Lihua; Lü Kevin; Liu Weiyi;
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作者单位

Yunnan University Department of Computer Science Kunming China;

Brunel University Uxbridge UK;

Yunnan University Department of Computer Science Kunming China;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类
关键词
social networks; community detection; cooperative game;

机译：社交网络;社区检测;合作博弈;

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专利

1. A novel two-step community detection approach based on community tree and the N-players cooperative game in large-scale social networks [J] . Decheng Zhang, Yakun Huang, Yang Wang, Journal of Computational Methods in Sciences and Engineering . 2018,第4期

机译：基于社区树的新型两步社区检测方法和大型社交网络中的N-Players合作游戏
2. An approach for overlapping and hierarchical community detection in social networks based on coalition formation game theory [J] . Zhou Lihua, Lu Kevin, Yang Peizhong, Expert Systems with Application . 2015,第24期

机译：基于联盟形成博弈理论的社交网络重叠分层社区检测方法
3. Dynamic subcarrier and power allocation based on cooperative game theory in symmetric cooperative OFDMA networks [J] . LIU Wei, LUO Tao, YUE Guang-xin 中国邮电高校学报（英文版） . 2011,第002期

机译：对称合作OFDMA网络中基于合作博弈的动态子载波和功率分配
4. A Game Theory Based Approach for Community Detection in Social Networks [C] . Lihua Zhou, Kevin Lue, Chao Cheng, Big data . 2013

机译：基于博弈论的社交网络社区发现方法
5. Cooperative game theory and community-based cooperatives. [D] . Strassburg, Jesse B. 2008

机译：合作博弈论和基于社区的合作社。
6. Game Theory and Extremal Optimization for Community Detection in Complex Dynamic Networks [O] . Rodica Ioana Lung, Camelia Chira, Anca Andreica 2010

机译：复杂动态网络中社区检测的博弈论与极值优化
7. An approach for overlapping and hierarchical community detection in social networks based on coalition formation game theory [O] . Lihua Zhou, Kevin Lü, Peizhong Yang, 2015

机译：基于联盟形成博弈论的社会网络重叠和分层社区检测方法

An approach for community detection in social networks based on cooperative games theory

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