Web2．0环境下社交网络信息传播仿真研究

A Simulation Study on Information Diffusion in Social Networks under Web2.0 Environment

本文分析了Web2．0环境下社交网络信息传播机理，借用复杂网络相关理论，构建了信息传播概念和数学模型，并进行计算机仿真。仿真结果表明：①在Web2．0环境下，一次信息传播中参与传播的用户占总用户数的比重一般不会超过65％，但传播规模即信息最终影响的用户数占比有时可以超过90％。②信息传播初始节点度会影响参与信息传播的用户数量及信息传播规模。③随着浏览概率阮从0．1增加到0．9，传播节点数和传播规模对初始传播节点度的变化曲线由线性增长逐渐向闭值性增长转变。④如果把马太效应引入到分享概率P，的取值设定上，那么这种逐渐的转变会分化为两类增长的极端：阈值性增长和线性增长。本文对于研究Web2．0环境下社交网络的信息传播活动有一定的理论价值和现实参考意义。

This paper aims at analyzing the information diffusion mechanism in social networks under Web2.0 environment. The paper builds conceptual and mathematical models for information diffusion based on the related theories of complex networks, and then conducts a simulation experiment study to test our model. The results of simulation experiment shows that： ①In a random diffusion process under Web2.0 environment, the proportion of the users who participate in spreading the information will not exceed 70% normally, but the proportion of diffusion scale accounts for more than 90% in some cases. ②The degree of initial diffusion node will positively affect the total number of users who spread the information and the diffusion scale. ③With the moderating of browse probability P2 from 0.1 to 0.9, the growth curves of the number of users who spread information and the diffusion scale change from linear growth pattern to threshold growth pattern. ④By introducing the Matthew Effect into the P3 data setting, the growth pattern polarizes into two categories interestingly ： linear growth and threshold growth. This paper has some theoretical contributions and practical implications for further research on information diffusion in social networks.