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李辉, 崔江涛, 马建峰. 一个三层次的在线网络社交影响研究综述[J]. 计算机科学技术学报, 2015, 30(1): 184-199. DOI: 10.1007/s11390-015-1512-7
引用本文: 李辉, 崔江涛, 马建峰. 一个三层次的在线网络社交影响研究综述[J]. 计算机科学技术学报, 2015, 30(1): 184-199. DOI: 10.1007/s11390-015-1512-7
Hui Li, Jiang-Tao Cui, Jian-Feng Ma. Social Influence Study in Online Networks: A Three-Level Review[J]. Journal of Computer Science and Technology, 2015, 30(1): 184-199. DOI: 10.1007/s11390-015-1512-7
Citation: Hui Li, Jiang-Tao Cui, Jian-Feng Ma. Social Influence Study in Online Networks: A Three-Level Review[J]. Journal of Computer Science and Technology, 2015, 30(1): 184-199. DOI: 10.1007/s11390-015-1512-7

一个三层次的在线网络社交影响研究综述

Social Influence Study in Online Networks: A Three-Level Review

  • 摘要: 社交网络分析将社会关系用图论的方式转变为节点和边来研究:用节点表示社交网络中的每个个体;边表示个体间的关系,包括朋友、通讯、信任等.这些关系受个体间的社交影响力驱动,这也正是社交网络区别于其他网络的最本质原因.在本文中,我们对驱动社交网络的社交影响力研究领域的研究成果进行了总结.本文将这些成果归纳为三层模型,即个体、社团和网络.通过本文对现有算法和模型的总结,我们可以揭示社交网络研究及其一系列应用的未来发展方向.

     

    Abstract: Social network analysis (SNA) views social relationships in terms of network theory consisting of nodes and ties. Nodes are the individual actors within the networks; ties are the relationships between the actors. In the sequel, we will use the term node and individual interchangeably. The relationship could be friendship, communication, trust, etc. These reason is that these relationships and ties are driven by social in uence, which is the most important phenomenon that distinguishes social network from other networks. In this paper, we present an overview of the representative research work in social in uence study. Those studies can be classi ed into three levels, namely individual, community, and network levels. Throughout the study, we are able to unveil a series of research directions in future and possible applications based on the state-of-the-art study.

     

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