复杂网络中多话题信息传播仿真研究

传统复杂网络话题传播研究,重点关注的是单个话题在网络中的传播,较少考虑多话题之间的相互影响因素。论文分析舆论传播过程中多个话题之间的竞争关系对话题传播的影响机制,建立基于复杂网络的多话题信息传播模型。通过对模型仿真实验及其结果分析表明,当引入个体信息环境影响因素后,一个话题的影响力大于舆论话题环境中其他话题的平均影响力,才会有较大概率影响到更多个体,否则只能在小范围内传播;个体对于话题记忆能力的变化在不同网络中会产生不同影响,在随机网络和BA网络中,人们对于话题的记忆越深,其传播的影响范围越大,而在规则网络和小世界网络中,较小的记忆长度能够让话题传播影响力更大;同时,在具有社群结构的网络中,度大的节点并非会一定会更多的参与某一话题的传播,因为度大的节点有更大概率获得更多的话题。

The Research of Multi Topic Dissemination in Complex Network

Most models about topic spreading lack the considerations of the effects between multi topics,and the main concern of the existing research model is the spread of a single topic in the network.In this paper,we consider the effects of competition between multi topics in the propagation process of public opinion top-ics,and propose a general model for the topics dissemination base on complex network.We simulate the in-formation spreading process,and analyze the experimental results.The results of simulation and of analysis show that some one topic will affecting more individuals if it＇s influence greater than the average influence of topics environment,otherwise,the topic will be spread between individuals neighbor; and,one topic will be spread wider range on random network and BA network if individuals have better memory,but in rule net-work and WS network,the opposite is true; at the same time,in a network with group structure,one node with larger degrees will not necessarily be more involved in the spread of the topic,because the node has bigger probability to receive more topics.