计算机科学 ›› 2022, Vol. 49 ›› Issue (6A): 280-284.doi: 10.11896/jsjkx.210500043
杜鸿毅, 杨华, 刘艳红, 杨鸿鹏
DU Hong-yi, YANG Hua, LIU Yan-hong, YANG Hong-peng
摘要： 针对目前已有网络信息传播模型都假设信息网络中所有已感染节点都会感染易感染节点,不能客观地反映信息传播具有时效性的问题,文中基于平均场理论,从信息传播的宏观角度出发,提出了一个新的网络媒体信息传播动力学模型。根据网络信息传播的实际情况,所提模型假设只有新感染的节点才会感染信息网络中易感染节点,而且易感染节点有两种途径变为已感染节点,一种是社交网络中已感染节点的传播,另一种是用户随机浏览。进一步地,基于图论理论将模型中节点的状态及其转换关系抽象为加权有向图,并且基于贝叶斯定理,将节点间的状态转换表示为概率事件,给出了事件发生的概率表达式,进而确定了状态转化关系矩阵。最后,运用高斯-赛德尔迭代法对模型进行数值求解,数值仿真结果表明,在线媒体信息传播具有时效性,热点事件会在一天之内达到传播高峰,之后传播范围迅速下降。紧接着,运用百度指数热点事件的统计数据对模型进行有效性验证,结果表明,所提模型比传统模型能更准确地反映网络信息的扩散趋势。
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