计算机应用 ›› 2015, Vol. 35 ›› Issue (3): 638-642.DOI: 10.11772/j.issn.1001-9081.2015.03.638

• 网络与通信 • 上一篇    下一篇

基于微博转发的社交网络模型

陈骁, 黄曙光, 秦李   

  1. 电子工程学院 网络系, 合肥 230037
  • 收稿日期:2014-10-20 修回日期:2014-11-19 出版日期:2015-03-10 发布日期:2015-03-13
  • 通讯作者: 陈骁
  • 作者简介:陈骁(1990-),女,安徽合肥人,硕士研究生,主要研究方向:复杂网络、社会网络;黄曙光(1960-),男,江苏海门人,教授,博士生导师,硕士,主要研究方向:复杂网络;秦李(1990-),男,四川绵阳人,硕士研究生,主要研究方向:复杂网络
  • 基金资助:

    安徽省自然科学基金资助项目(1208085QF107)

Social network model based on micro-blog transmission

CHEN Xiao, HUANG Shuguang, QIN Li   

  1. Department of Network, Electronic Engineering Institute, Hefei Anhui 230037, China
  • Received:2014-10-20 Revised:2014-11-19 Online:2015-03-10 Published:2015-03-13

摘要:

探究微博转发网络的构建机制有助于深刻理解信息在微博平台上的传播过程,得出针对微博营销、舆论管控的有效策略和建议。针对这一问题,提出了一种有向加权网络模型。根据微博在转发过程中被多次转发的现象,在模型建立过程中,在节点间连边时引入三角连接机制,并且用连边的方向选择表征了活跃用户和知名用户的不同行为特征,同时考虑了权值的动态演化过程。理论分析和仿真实验表明模型的强度分布、度分布、强度-度的相关性均服从幂律分布,幂指数为1~3,而且具有高聚类、短路径的特点,平均聚类系数可达0.42,平均路径长不超过6,同时采集了微博转发的实际数据验证了模型的正确性。

关键词: 微博转发网络, 有向加权网络, 拓扑性质, 三角构成规则, 幂律分布

Abstract:

Studying the constructing mechanism of micro-blog transmission network help to understand the information spreading process on the micro-blog platform deeply, and then obtain effective strategies and suggestions. As for this issue, a directed and weighted network model was proposed. In the model building process, according to the phenomenon that micro-blogs can be transmitted more than one time, triad formation was introduced. Different directions of links were used to represent the various characteristics of active and famous users. Besides, the dynamic evolution process of the link weight was considered. The theory analysis and simulation experiment results indicate the strength distribution, the degree distribution and the correlation of strength and degree obey power-law distribution, and the power exponents are between 1 and 3. Also, this model is characterized by high clustering coefficient and short average path length. Average clustering coefficient is 0.7, and average length is less than 6. As well, actual data of micro-blog transmission were collected to prove the model's correctness.

Key words: micro-blog transmission network, directed and weighted network, topology property, Triad Formation (TF) rule, power-law distribution

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