期刊文献+

基于复杂网络理论的微博信息传播实证分析 被引量:52

The Empirical Analysis of Micro-blog Information Flow Based on Complex Network Theory
原文传递
导出
摘要 为研究信息在微博中的传播特征,对新浪微博数据进行实证分析。利用复杂网络理论方法,对构建的微博信息传播网络,进行基于度、路径统计指标的分析,发现该网络具有集群性、小世界、高度中心化等特征。这些特征表明,信息在微博网络中的传播效率比其他在线社会网络更高;网络中介数中心点对信息传播效率的贡献显著,但网络并不脆弱;节点在信息传播中的作用差异很大,易于形成意见领袖。按行业属性对网络进行群落划分后,发现各群落在微博中表现出的信息传播特性与在现实社会中相似。 In order to study the features of micro-blog information flow, the authors make empirical analysis on Sina micro-blog data. Using complex network theory, they analyze indicators of information flow network based on degree and path statistical indexes and find that the network has clustery, small world, highly polarized features, etc. These features show that information flow efficiency in micro- blog is higher than other online social networks; the vertex betweenness-first center contributes to efficiency significantly, but the network is not vulnerable ; node is very difference in the role of information flow, easy to form opinions leader. After dividing the network accord- ing to industrial property, the authors find information flow features of community in micro-blog are similar to in actual society.
作者 田占伟 隋玚
出处 《图书情报工作》 CSSCI 北大核心 2012年第8期42-46,共5页 Library and Information Service
关键词 复杂网络 微博 信息传播 网络结构分析 complex network micro-blog information transmission network structure analysis
  • 相关文献

参考文献22

  • 1Wasserman S,Faust K. Social network analysis:Methods and applications[M].Cambridge:Cambridge University Press,1994.1-3.
  • 2Dunbar R I M. Coevolution of neocortical size,group size and language in humans[J].Behavioral and Brain Sciences,1993,(04):681-735.
  • 3Milgram S. The small-world problem[J].Psychology Today,1967,(01):61-67.
  • 4胡海波,徐玲,王科,汪小帆.大型在线社会网络结构分析[J].上海交通大学学报,2009,43(4):587-591. 被引量:28
  • 5Ravasz E,Barabsi A L. Hierarchical organization in complex networks[J].Physical Review E,2003,(02):1-7.
  • 6Golder S A,Wilkinson D M,Huberman B A. Rhythms of social interaction:Messaging within a massive online network[A].London:Springer-Verlag,2007.41-66.
  • 7Zakharov P. Thermodynamic approach for community discovering within the complex networks:Live Journal study[J].Arxiv:physics,2006,(01):1-8.
  • 8Fu Feng,Chen Xiaojie,Liu Lianghuan. Social dilemmas in an online social network:The structure and evolution of cooperation[J].Physics Letters A,2007,(01):58-64.
  • 9Kumar R,Novak J,Tomkins A. Structure and evolution of online social networks[A].Philadelphia:ACM,2006.611-617.
  • 10Lerman K. Social information processing in news aggregation[J].IEEE Internet Computing,2007,(06):16-28.

二级参考文献73

  • 1张睿,汪克夷,夏立坤,刘佑铭.企业市场知识能力、营销能力及组织绩效间关系研究[J].大连理工大学学报(社会科学版),2008,29(2):19-24. 被引量:10
  • 2江文年,杨建梅.基于多视角知识演化的企业知识管理体系研究[J].科技管理研究,2004,24(4):65-67. 被引量:9
  • 3周涛,柏文洁,汪秉宏,刘之景,严钢.复杂网络研究概述[J].物理,2005,34(1):31-36. 被引量:243
  • 4方锦清.非线性网络的动力学复杂性研究的若干进展[J].自然科学进展,2007,17(7):841-857. 被引量:21
  • 5Costa L da F, Rodrigues F A, Travieso G, et al. Characterization of complex networks: A survey of measurements [J]. Advances in Physics, 2007, 56(1): 167-242.
  • 6Xu X P, Hu J H, Liu F. Complex network study of Asian Go players [J]. CHAOS, 2007, 17: 023111.
  • 7Clauset A, Newman M E J, Moore C. Finding community structure in very large networks [J]. Phys Rev E, 2004, 70, 066111.
  • 8Mislove A, Marcon M, Gummadi K P, et al. Measurement and analysis of online social networks[C]// Proceedings of the 7th ACM SIGCOMM Conference on Internet Measurement. New York: ACM Press, 2007: 29-42.
  • 9Gold A H, Malhotra A, Segars A H. Knowledge management : an organizational capabilities perspective. Journal of Management Information Systems,2001,18 ( 1 ) : 185 - 214.
  • 10Hunt S D, Robert M M. The comparative advantage theory of competition. Journal of Marketing, 1995,59 (2) : 1 - 15.

共引文献175

同被引文献751

引证文献52

二级引证文献434

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部