计算机科学 ›› 2021, Vol. 48 ›› Issue (7): 118-123.doi: 10.11896/jsjkx.200600155
桑春艳1, 胥文1, 贾朝龙1, 文俊浩2
SANG Chun-yan1, XU Wen1, JIA Chao-long1, WEN Jun-hao2
摘要: 与传统媒体相比,社交网络在传播新闻、思想、观点等方面发挥着突出的作用,同时也是传播谣言、虚假新闻等负面信息的最佳途径。因此,对网络舆情演化趋势的准确预测和有效控制已成为重要的研究话题。目前,大多数研究从理论建模的角度对网络舆情事件的演化特性和发展趋势进行预测,基于用户行为特征的信息传播演化趋势预测模型的建模及分析有待进一步研究。考虑到信息传播过程中用户之间的相互影响,文中提出一种基于注意力机制的方法,旨在探究社交网络中用户在信息传播过程中的影响来预测信息的传播趋势。首先,利用基于长短时记忆神经网络(Long Shot-Term Memory,LSTM)的网络架构来获取信息传播的轨迹特征。其次,考虑到信息传播和用户行为的复杂性,利用注意力机制挖掘用户之间的依赖性来预测真实的信息传播过程。最后,综合考虑影响信息传播的驱动因素,得到一种基于注意力机制的信息传播演化趋势预测模型(Attention Diffusion Neural Network,ADNN)。在4个对比数据集上的实验结果显示,ADNN模型优于流行的序列模型,该模型能够有效利用驱动因素对信息传播的影响,更准确地预测社交网络中信息的传播趋势。
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