虚拟社区中兴趣传播模型的研究
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摘要
随着近年来BBS电子公告栏和SNS社区网络的风靡,越来越多的网民参与到各式各样的网络虚拟社区中,以虚拟人的身份在虚拟社区中与进行话题交流和兴趣分享。这种交流和分享把网络虚拟人紧密的联系起来,形成了庞大的复杂网络。在这个复杂网络中,虚拟人如何相互影响、兴趣主题如何传播等问题受到了广泛的关注,并衍生出观点动力学等一系列理论。本文以复杂网络理论为基础,借鉴观点动力学的内容,对网络虚拟社区中的兴趣传播规律进行了研究。
本论文主要讨论分享类网络虚拟社区,以豆瓣网虚拟社区为实验数据来源,使用爬虫技术获取其网页原始数据,并使用预处理程序对原始数据进行过滤、分析。利用处理后的最终数据,本文对网络虚拟社区和其中的虚拟人成员分别进行了建模研究。其中对豆瓣网虚拟社区的拓扑研究使用了复杂网络和社会网络分析法,模型中以虚拟人成员为节点、虚拟人之间的好友关系为连线。同时讨论了此网络虚拟社区的相关特征参数,包括平均最短路径、聚类系数、度分布的仿真研究,最终验证了豆瓣网虚拟社区符合无标度网络特征。对虚拟人的建模则基于组织行为学,并参考了国内外关于网络虚拟人行为特征的相关研究,将网络虚拟人成员分为：享受者、奉献者、交际者三个类别。
接下来本文对疾病传播模型SIR模型进行了改进,提出了适合网络虚拟社区的兴趣传播模型,通过程序仿真的方法模拟了兴趣主题在网络社区中的传播特性和各虚拟人节点的状态转换规律,并通过豆瓣网实际数据验证了此模型的合理性和实用性。
In recent years, as BBC and SNS prevail in Internet community, more and more netizens have been joining various virtual communities online. They communicate and share stuffs of interest in these communities as virtual persons, and therefore weave a giant and complex network. The pattern that virtual people affect each other and disseminate interest drew wide attention and opinion-dynamics came into being. This paper probes into the law of dissemination of interest from opinion-dynamic perspective.
This paper focus on the Internet community which is famous for its sharing and takes data from Douban.com as the subject for study. The writer collected original data by crawler and used preprocessor to select information for analyzing. The analysed data have been used in modeling to look into the Internet community and its members. Complex network and social network analytic approach is used in the modeling of Douban.com. In this model, virtual persons are dots and friendships between them are lines. This paper also includes discussion of parameters of related features in virtual community, such as simulation study on average shortest-paths, clustering coefficient and degree distribution. As a result, it proves that Douban.com fits the features of scale-free network. The virtual persons model is built under the theory of organizational behaviour, has consulted researches concerning the features of virtual human behaviour on the Internet and divides virtual community members into three categories:receiver, dedicator and raver.
This paper continued to present an interest dissemination model, which is altered from disease dissemination model known as SIR. It simulates the spread of interest themes and the state changing pattern of virtual individuals by program stimulation. This model is proved reasonable and practical by factual data from Douban.com.
本论文主要讨论分享类网络虚拟社区,以豆瓣网虚拟社区为实验数据来源,使用爬虫技术获取其网页原始数据,并使用预处理程序对原始数据进行过滤、分析。利用处理后的最终数据,本文对网络虚拟社区和其中的虚拟人成员分别进行了建模研究。其中对豆瓣网虚拟社区的拓扑研究使用了复杂网络和社会网络分析法,模型中以虚拟人成员为节点、虚拟人之间的好友关系为连线。同时讨论了此网络虚拟社区的相关特征参数,包括平均最短路径、聚类系数、度分布的仿真研究,最终验证了豆瓣网虚拟社区符合无标度网络特征。对虚拟人的建模则基于组织行为学,并参考了国内外关于网络虚拟人行为特征的相关研究,将网络虚拟人成员分为：享受者、奉献者、交际者三个类别。
接下来本文对疾病传播模型SIR模型进行了改进,提出了适合网络虚拟社区的兴趣传播模型,通过程序仿真的方法模拟了兴趣主题在网络社区中的传播特性和各虚拟人节点的状态转换规律,并通过豆瓣网实际数据验证了此模型的合理性和实用性。
In recent years, as BBC and SNS prevail in Internet community, more and more netizens have been joining various virtual communities online. They communicate and share stuffs of interest in these communities as virtual persons, and therefore weave a giant and complex network. The pattern that virtual people affect each other and disseminate interest drew wide attention and opinion-dynamics came into being. This paper probes into the law of dissemination of interest from opinion-dynamic perspective.
This paper focus on the Internet community which is famous for its sharing and takes data from Douban.com as the subject for study. The writer collected original data by crawler and used preprocessor to select information for analyzing. The analysed data have been used in modeling to look into the Internet community and its members. Complex network and social network analytic approach is used in the modeling of Douban.com. In this model, virtual persons are dots and friendships between them are lines. This paper also includes discussion of parameters of related features in virtual community, such as simulation study on average shortest-paths, clustering coefficient and degree distribution. As a result, it proves that Douban.com fits the features of scale-free network. The virtual persons model is built under the theory of organizational behaviour, has consulted researches concerning the features of virtual human behaviour on the Internet and divides virtual community members into three categories:receiver, dedicator and raver.
This paper continued to present an interest dissemination model, which is altered from disease dissemination model known as SIR. It simulates the spread of interest themes and the state changing pattern of virtual individuals by program stimulation. This model is proved reasonable and practical by factual data from Douban.com.
引文
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[14]Sergio Rodrigues,Jonice Oliveira,Jano M.de Souza. Recommendation for Team and Virtual Community Formations Based on Competence Mining.
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[19]夏承遗,刘忠信,陈增强等.复杂网络的传播动力学及其新进展.智能系统学报.2009.10.
[20]王延,郑志刚.无标度网络上的传播动力学.物理学报.2009.7.
[21]Yamir Moreno,Maziar Nekovee,etc. Dynamics of rumor spreading in complex networks.Physical Review.2004.6.
[22]陈海强,程学旗,刘悦.基于用户兴趣的寻找虚拟社区核心成员的方法.中文信息学报.2009.3.
[23]Liang Zhao,Katti Faceli,etc.Data Clustering Based on Complex Network Community Detection.IEEE Congress on Evolutionary Computation.2008.
[24]Aixiang Cui,Duanbing Chen,Yan Fu. Community detection based on weighted networks. IFIP International Conference on Network and Parallel Computing.2008.
[25]D.Stauffer,A.O.Sousa,C.Schulze. Discretized opinion dynamics of Deffuant model on scale-free networks. ArXiv.cond-mat.2004.3.
[26]官山,朱陈平,刘宗华等.复杂网络动力学框架的几个研究方向.复杂系统与复杂性科 学.2008.9.
[27]张立,刘云.网络舆情传播的无标度特性及其衰减模型的研究.北京交通大学学报.2008.4.
[28]杜海峰,李树茁.小世界网络和无标度网络的社区结构研究.物理学报.2007.12.
[29]Bergami,M.and Bagozzi R.P.Intentional social action in virtual communities.Journal of Interactive MarKeting,2002.16(2).
[30]Armstrong,A.and Hagel.Expanding Markets Through Virtual Communities,Simon &Schuster Inc.1997.
[31]Barabasi A.L.Albert R.Emergence of scaling in random networks.Science,1999,286(5439).
[32]蒋凡.基于虚拟社区的Web挖掘技术研究[学位论文].合肥.中国科学技术大学.
[33]麦林.虚拟社区热点话题意见挖掘模型研究[学位论文].合肥.中国科学技术大学.
[2]柴晋颖,王飞绒.虚拟社区研究现状与展望.情报杂志.2007.5.
[3]陈莉,焦李成.Internet/Web数据挖掘研究现状及最新进展.西安电子科技大学学报.2001.2
[4]金晓鸥.互联网舆情信息获取与分析研究[学位论文].上海.上海交通大学.
[5]李舒辰,刘云,李勇.网络舆情分析中网页信息预处理方案的实现.学术探讨基金项目.
[6]王林,戴冠中.基于复杂网络社区结构的论坛热点主题发现.计算机工程.2008.6.
[7]Newman, S.H. Strogatz, D.J.Watts, Random graph with arbitrary degree distribution and their applications. Phys.Rev.E,64 2001.
[8]Duncan J.Watts,Steven H.Strogatz. Collective dynamics of small-world' networks.letters of nature.2004.6.
[9]D.J.Watts. Small World. Princeton University Press, Princeton,1990.
[10]阮冰,朱建冲等.复杂网络上的舆论形成演化建模与仿真研究.军事运筹与系统工程.2010.3.
[11]Lianhong Ding,Xiang Li,Yunpeng Xing. Pushing Scientific Documents by Discovering Interest inInformation Flow Within E-Science Knowledge Grid.
[12]付丽丽,吕本富,吴盈廷等.关系型虚拟社区社会网络特征研究.数学的实践与认识.2009.1.
[13]荣波,夏正友等.BBS在线复杂网络及其成员交互特性研究.复杂系统与复杂性科学.2009.12.
[14]Sergio Rodrigues,Jonice Oliveira,Jano M.de Souza. Recommendation for Team and Virtual Community Formations Based on Competence Mining.
[15]Dholakia,U.M.Bagozzi.A social influence model of consumer participation in network and small-group-based virtual communities.International Journal of Research in Marketing,2004.21.
[16]Eunyoung Cheon,JoongHo Ahn.know your virtual community and members. Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication 2009.
[17]Moukarzel C.F.Spreading and shortest paths in systems with sparse long-range connections.Phys.Rev.E,1999,60:R6263.
[18]李光正,史定华.复杂网络上SIRS类疾病传播行为分析.自然科学进展.2006.4.
[19]夏承遗,刘忠信,陈增强等.复杂网络的传播动力学及其新进展.智能系统学报.2009.10.
[20]王延,郑志刚.无标度网络上的传播动力学.物理学报.2009.7.
[21]Yamir Moreno,Maziar Nekovee,etc. Dynamics of rumor spreading in complex networks.Physical Review.2004.6.
[22]陈海强,程学旗,刘悦.基于用户兴趣的寻找虚拟社区核心成员的方法.中文信息学报.2009.3.
[23]Liang Zhao,Katti Faceli,etc.Data Clustering Based on Complex Network Community Detection.IEEE Congress on Evolutionary Computation.2008.
[24]Aixiang Cui,Duanbing Chen,Yan Fu. Community detection based on weighted networks. IFIP International Conference on Network and Parallel Computing.2008.
[25]D.Stauffer,A.O.Sousa,C.Schulze. Discretized opinion dynamics of Deffuant model on scale-free networks. ArXiv.cond-mat.2004.3.
[26]官山,朱陈平,刘宗华等.复杂网络动力学框架的几个研究方向.复杂系统与复杂性科 学.2008.9.
[27]张立,刘云.网络舆情传播的无标度特性及其衰减模型的研究.北京交通大学学报.2008.4.
[28]杜海峰,李树茁.小世界网络和无标度网络的社区结构研究.物理学报.2007.12.
[29]Bergami,M.and Bagozzi R.P.Intentional social action in virtual communities.Journal of Interactive MarKeting,2002.16(2).
[30]Armstrong,A.and Hagel.Expanding Markets Through Virtual Communities,Simon &Schuster Inc.1997.
[31]Barabasi A.L.Albert R.Emergence of scaling in random networks.Science,1999,286(5439).
[32]蒋凡.基于虚拟社区的Web挖掘技术研究[学位论文].合肥.中国科学技术大学.
[33]麦林.虚拟社区热点话题意见挖掘模型研究[学位论文].合肥.中国科学技术大学.