Abstract: In the information propagation research of social network, it is the most common way to set up a propagation probability and simulate the information propagation by using various models. However, the appointed propagation probability has a great influence on the propagation. Based on the idea of finding important nodes in complex networks, this paper presents a method to calculate the probability of propagation. Experiment analyzes different results caused by the fixed propagation probability and the probability with influence of origin, and shows the calculated probability more satisfies the truth by validating the algorithm of node’s influence.

Key words: social network, information propagation probability, influence

摘要： 在社交网络上的信息传播的研究中，设定一个传播概率，运用各种传播模型来模拟信息传播过程，是最常见的一种方式，然而人为设定的传播概率对传播过程有很大影响。根据复杂网络的相关研究，计算信息源节点的影响力，并以此为基础提出了一种计算信息传播概率的方法。实验对比了人为设定的传播概率与考虑了信息源节点影响力的传播概率对传播结果造成的差异，并通过证明影响力算法的有效性，说明了计算后的传播概率更加合理。

关键词: 社交网络, 信息传播概率, 影响力