目前社会群体研究主要集中在将群体划分为多个社区。然而,在一个群体中,通常希望所有的成员团结一致,形成一个具有凝聚力的群体,这对社会群体的合作以及社会习俗形成等相关研究具有广泛意义。因此理解社会凝聚力与社会群体的动态行为之间的关系显得十分重要。该文在合作博弈的基础上,建立了社会群体动态行为模型。基于传统网络拓扑结构,该文研究了在社会群体中增强凝聚力的策略,提出了基于最大团的CPMC和CPIN算法,通过特定的干预机制,将整体划分为两层,选择边缘层节点加入核心层,同时增加节点之间的链接,从而使社会群体具有更好的社会凝聚力,并且通过实验验证了算法的有效性。
Abstract
It is crucial to understand the relation between social cohesion and the dynamic behavior of social groups. A model of social group dynamics is explored on the basis of cooperative games. Based on the classical network topology structure, this paper investigates the strategy of enhancing cohesion among social groups, and proposes the CPMC and CPIN algorithms which involve the largest clique. Through a specific intervention mechanism, the whole network is divided into two layers, and periphery nodes are selected to join the core layer. Increasing the links between nodes at the same time, the social groups are demonstrated for a better social cohesion.
关键词
社会网络 /
合作博弈 /
网络结构
{{custom_keyword}} /
Key words
social network /
cooperative game /
network structure
{{custom_keyword}} /
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] Tajfel H.Social identity and intergroup relations[M]. Cambridge University Press, 2010.
[2] 许丹青,刘奕群,张敏,等.基于在线社会网络的用户影响力研究[J].中文信息学报,2016,30(2): 83-90.
[3] Backstrom L,Huttenlocher D, Kleinberg J, et al. Group formation in large social networks: membership, growth, and evolution[C]//Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data mining,Philadelphia, PA, USA, ACM Press, 2006: 44-54.
[4] Nowak A, Vallacher R R, Miller M E. Social influence and group dynamics[M]. Handbook of Psychology, 2003: 383-417.
[5] 吴安彪,袁野,乔百友,等.大规模时序图影响力最大化的算法研究[J]. 计算机学报, 2019,42(12): 2647-2664.
[6] White D R,Harary F. The cohesiveness of blocks in social networks: Node connectivity and conditional density[J]. Sociological Methodology, 2001, 31(1): 305-359.
[7] Beal D J, Cohen R R, Burke M J, et al. Cohesion and performance in groups: A meta-analytic clarification of construct relations[J]. Journal of Applied Psychology, 2003, 88(6): 989-1004.
[8] Purohit H,Ruan Y, Fuhry D, et al. On the role of social identity and cohesion in characterizing online social communities[J]. arXiv preprint arXiv:1212.0141, 2012.
[9] Gharehshiran O N, Krishnamurthy V. Coalition formation for bearings-only localization in sensor networks: A cooperative game approach[J]. IEEE Transactions on Signal Processing, 2010, 58(8): 4322-4338.
[10] Massin R, Le Martret C J, Ciblat P. A coalition formation game for distributed node clustering in mobile ad hoc networks[J]. IEEE Transactions on Wireless Communications, 2017, 16(6): 3940-3952.
[11] Apt K R, Witzel A. A generic approach to coalition formation[J]. International Game Theory Review, 2009, 11(03): 347-367.
[12] Aziz H,Brandl F, Brandt F, et al. Fractional hedonic games[J]. ACM Transactions on Economics and Computation (TEAC), 2019, 7(2): 1-29.
[13] Alvin W Wolfe. Social network analysis: Methods and applications[J]. American Ethnologist, 2008.
[14] Zhang K, Du H, Feldman M W. Maximizing influence in a social network: Improved results using a genetic algorithm[J]. Physica A: Statal Mechanics and its Applications, 2017, 478: 20-30.
[15] Jiang R, Liu J, Chen W.How to improve the cohesion of a social network? A Structural perspective[C]//Proceedings of the 7th International Symposium on Computing and Networking (CANDAR). IEEE, 2019: 143-149.
[16] Liu J, Wei Z.Network, popularity and social cohesion: Agame-theoretic approach[C]//Proceedings of the 31st AAAI Conference on Artificial Intelligence, San Francisco, California, USA, AAAI, 2017: 600-606.
[17] Moskvina A, Liu J. How to build your network? a structural analysis[C]//Proceedings of the 25th International Joint Conference on Artificial Intelligence, New York, NY, USA, IJCAI/AAAI, 2016: 2597-2603.
[18] Csermely P, London A, Wu L Y, et al. Structure and dynamics of core/periphery networks[J]. Journal of Complex Networks, 2013, 1(2): 93-123.
[19] Borgatti S P, Everett M G. Models of core/periphery structures[J]. Social Networks, 2000, 21(4): 375-395.
[20] Ma H W, Zeng A P. The connectivity structure, giant strong component and centrality of metabolic networks[J]. Bioinformatics, 2003, 19(11): 1423-1430.
[21] Seidman S B. Network structure and minimum degree[J]. Social Networks, 1983, 5(3):269.
[22] Zhou S, Mondragon R J. The rich-club phenomenon in the Internet topology[J].IEEE Communications Letters, 2004, 8(3):180-182.
[23] 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.
[24] Gleiser P, Danon L. List of edges of the network of Jazz musicians[J]. Adv. Complex Systems, 2003, 6: 565.
[25] MacRae D. Direct factor analysis of sociometric data[J]. Sociometry, 1960, 23(4): 360-371.
[26] Rossi R, Ahmed N. The network data repository with interactive graph analytics and visualization[C]//Proceedings of the 29th AAAI Conference on Artificial Intelligence, Austin, Texas, USA, AAAI, 2015: 4292-4293.
{{custom_fnGroup.title_cn}}
脚注
{{custom_fn.content}}
基金
重庆市人文社会科学重点研究基地项目(18SKB047);中央高校基本科研业务费重点项目(XDJK2019B063)
{{custom_fund}}
PDF(3867 KB)
