[1]王景丽,许立波,庞超逸.复杂网络中的在线社交网络演化模型[J].智能系统学报编辑部,2015,(6):949-953.[doi:10.11992/tis.201507042]
 WANG Jingli,XU Libo,PANG Chaoyi.Evolution model of online social networks based on complex networks[J].CAAI Transactions on Intelligent Systems,2015,(6):949-953.[doi:10.11992/tis.201507042]
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复杂网络中的在线社交网络演化模型(/HTML)
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《智能系统学报》编辑部[ISSN:1673-4785/CN:23-1538/TP]

卷:
期数:
2015年6期
页码:
949-953
栏目:
出版日期:
2015-12-25

文章信息/Info

Title:
Evolution model of online social networks based on complex networks
作者:
王景丽1 许立波2 庞超逸3
1. 宁波大红鹰学院信息工程学院, 浙江宁波 315175;
2. 浙江大学宁波理工学院, 浙江宁波 315000;
3. 浙江大学宁波理工学院, 浙江宁波 315000
Author(s):
WANG Jingli1 XU Libo2 PANG Chaoyi3
1. Information Engineering, Ningbo Dahongying University, Ningbo 315175, China;
2. Research Center on Intelligent Computing and Data Management Ningbo Institute of Technology, Zhejiang University, Ningbo 315000, China;
3. Research Center on Intellig
关键词:
复杂网络社交网络度分布幂率分布演化平均场节点度拓扑
Keywords:
complex networksocial networkdegree distributionpower-law distributionevolutionmean fieldnode degreetopology
分类号:
TP393
DOI:
10.11992/tis.201507042
摘要:
在线社交网络是一种广泛存在的社会网络,其节点度遵循幂率分布规律,但对于其结构演化模型方面的相关研究还不多。基于复杂网络理论研究在线社交网络内部结构特征,提出一种结合内增长、外增长及内部边更替的演化模型,借助平均场理论分析该模型的拓扑特性,实验和理论分析表明由该模型生成的网络,其度分布服从幂率分布,且通过调整参数,幂率指数在1~3,能较好地反映不同类型的真实在线社交网络的度分布特征,因此具有广泛适用性。
Abstract:
As a widespread social network, the node degree of online social networks has been proven by many researchers to follow the power-law distribution. However, there are few studies modeling the evolution of its structure. In this paper, we propose an evolution model that combines the inside growth, outside growth, and edge replacement based on those of complex networks. The topology properties of this model are analyzed using the mean-field theory. Experiment and theoretical analyses show that the degree of a node in a network generated by the new evolution model follows the power-law distribution and that the power-law index ranges between 1 and 3. Therefore, the proposed model can better reflect the node degree distribution characteristics of different types of real online social networks and will have wide applicability.

参考文献/References:

[1] WATTS D J, STROGATZ S H. Collective dynamics of ’small-world’ networks[J]. Nature, 1998, 393(6684):440-442.
[2] BARABASI A L, ALBERT R. Emergence of scaling in random networks[J]. Science, 1999, 286(5439):509-512.
[3] FALOUTSOS M, FALOUTSOS P, FALOUTSOS C. On power-law relationships of the Internet topology[J]. ACM SIGCOMM Computer Communication Review Homepage, 1999, 29(4):251-262.
[4] ALBERT R, BARABASI A L. Topology of evolving networks:local events and universality[J]. Physical Review Letters 2000, 85(24):5234-5237.
[5] BU T, TOWSLEY D. On distinguishing between Internet power law topology generators[C]//Proceedings of INFOCOM 2002. Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies. New York, NY:IEEE, 2002, 2:638-647.
[6] PARK S T, PENNOCK D M, GILES C L. Comparing static and dynamic measurements and models of the Internet’s as topology[C]//Proceedings of the 23rd Annual Joint Conference of the IEEE Computer and Communications Societies. Hong Kong:IEEE, 2004, 3:1616-1627.
[7] CHEN Guangrong, FAN Zhenping, LI Xiang. Modeling the complex Internet topology[C]//KOCAREV L, VATTAY G. Complex Dynamics in Communication Networks. Berlin Heidelberg:Springer, 2005.
[8] 田思, 李慧嘉, 赵岳. 一种新型多局域世界网络模型分析[J]. 计算机应用研究, 2013, 30(3):869-872. TIAN Si, LI Huijia, ZHAO Yue. Analysis of novel multi-local world network model[J]. Application Research of Computers, 2013, 30(3):869-872.
[9] NEWMAN M E J. The structure of scientific collaboration networks[C]. Proceedings of National Academy Sciences, 2001, 98(2):404-409.
[10] MYERS C R. Software systems as complex networks:structure, function, and evolvability of software collaboration graphs[J]. Physical Review E, 2003, 68(4Pt2):046116.
[11] JEONG H, MASON S P, BARABASI A L, et al. Lethality and centrality in protein networks[J]. Nature, 2001, 411(6833):41-42.
[12] 王亚奇, 王静, 杨海滨. 基于复杂网络理论的微博用户关系网络演化模型研究[J]. 物理学报, 2014, 63(20):208902. WANG Yaqi, WANG Jing, YANG Haibin. An evolution model of microblog user relationship networks based on complex network theory[J]. Acta Physica Sinica, 2014, 63(20):208902.
[13] 刘浩然, 尹文晓, 董明如, 等. 一种强容侵能力的无线传感器网络无标度拓扑模型研究[J]. 物理学报, 2014, 63(9):090503. LIU Haoran, YIN Wenxiao, DONG Mingru, et al. Study on the scale-free topology model with strong intrusion-tolerance ability in wireless sensor networks[J]. Acta Physica Sinica, 2014, 63(9):090503.
[14] SOLE R V, PASTOR-SATORRAS R, SMITH E, et al. A model of large-scale proteome evolution[J]. Advances in Complex Systems, 2002, 5(1):43-54.
[15] 维基选举社交网络..http://www.linkprediction.org/index.php/link/resource/data.
[16] 汪培庄. 因素空间与因素库[J]. 辽宁工程技术大学学报:自然科学版, 2013, 32(10):1297-1304. WANG Peizhuang. Factor spaces and factor data-bases[J]. Journal of Liaoning Technical University:Natural Science, 2013, 32(10):1297-1304.
[17] 汪培庄. 因素空间与数据科学[J]. 辽宁工程技术大学学报:自然科学版, 2015, 34(2):273-280. WANG Peizhuang. Factor spaces and data science[J]. Journal of Liaoning Technical University:Natural Science, 2015, 34(2):273-280.

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备注/Memo

备注/Memo:
收稿日期:2015-07-05;改回日期:。
基金项目:国家自然科学基金资助项目(71271191);宁波市自然科学基金资助项目(2015A610138).
作者简介:王景丽,女,1981年生,讲师。主要研究方向为复杂网络。许立波,男,1976年生,讲师,博士。主要研究方向为复杂网络、overlay网络。
通讯作者:王景丽.E-mailjingli.wang@nbdhyu.edu.cn.
更新日期/Last Update: 1900-01-01