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在线社交网络中信息传播模式的特征分析
引用本文:韩佳,肖如良,胡耀,唐涛,房丽娜. 在线社交网络中信息传播模式的特征分析[J]. 计算机应用, 2013, 33(1): 105-107. DOI: 10.3724/SP.J.1087.2013.00105
作者姓名:韩佳  肖如良  胡耀  唐涛  房丽娜
作者单位:1. 福建师范大学 软件学院, 福州 3501082. 深圳信息职业技术学院 软件学院, 广东 深圳 518172
基金项目:教育部规划基金资助项目(11YJA860028);福建省科技计划重大项目(2011H6006)
摘    要:在线社交网络以其独特的传播优势,已成为一种流行的社交媒体平台。针对在线社交网络中信息传播模式的形式特点,结合传染病动力学原理,提出了在线社交网络中的信息传播模型。模型考虑了不同用户行为对传播机理的影响,并建立了不同用户节点的演化方程组,模拟了信息传播的过程,分析了不同类型的用户在网络中的行为特征以及影响信息传播的主要因素。实验结果表明:不同类型的用户在信息传播过程中有着特定的行为规律,信息不会无限制地传播,并在最终达到平稳状态,并且传播系数和免疫系数越大,信息传播达到稳态的速度就越快。

关 键 词:在线社交网络  信息传播  传播模式  特征分析  
收稿时间:2012-07-04
修稿时间:2012-08-09

Characteristic analysis of information propagation pattern in online social network
HAN Jia,XIAO Ruliang,HU Yao,TANG Tao,FANG Lina. Characteristic analysis of information propagation pattern in online social network[J]. Journal of Computer Applications, 2013, 33(1): 105-107. DOI: 10.3724/SP.J.1087.2013.00105
Authors:HAN Jia  XIAO Ruliang  HU Yao  TANG Tao  FANG Lina
Affiliation:1. Faculty of Software, Fujian Normal University, Fuzhou Fujian 350108, China
2. Department of Software, Shenzhen Institute of Information Technology, Shenzhen Guangdong 518172, China
Abstract:Because of its unique advantage of information propagation, the online social network has been a popular social communication platform. In view of the characteristics of the form of information propagation and the dynamics theory of infectious diseases, this paper put forward the model of information propagation through online social network. The model considered the influence of different users' behaviors on the transmission mechanism, set up the evolution equations of different user nodes, simulated the process of information propagation, and analyzed the behavior characteristics of the different types of users and main factors that influenced the information propagation. The experimental results show that different types of users have special behavior rules in the process of information propagation, i.e., information cannot be transported endlessly, and be reached at a stationary state, and the larger the spread coefficient or immune coefficient is, the faster it reached the stationary state.
Keywords:online social network   information propagation   transmission pattern   characteristic analysis
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