Abstract: With the rapid development of social networks, microblog has become a platform for the spread of information dissemination. In view of the characteristics of microblog information diffusion, mining the potential law of microblog forwarding process is of great significance for public opinion monitoring, hot topic tracking, product marketing and so on. In this paper, the Sina microblog is used as the data source, the user and microblog content are used as the characteristic source. The neural network prediction algorithm in machine learning is introduced to establish the prediction model to realize the forward prediction of microblog. The results show that, compard with the traditional prediction method, the microblog forwarding can make a higher accuracy prediction.

Key words: Neural network, BP algorithm, LDA, Predictive modeling

摘要： 随着社交网络的快速发展,微博已成为一种信息扩散传播的平台。鉴于微博信息扩散的特点,挖掘微博转发过程中的潜在规律对于舆情监控、热点话题追踪、产品营销等有着重要意义。以新浪微博作为数据源,以用户和微博内容作为特征源,引入机器学习中的神经网络预测算法建立预测模型,实现对微博的转发预测。结果表明,与传统预测方法的对比,对微博转发可以做出较高准确率的预测。

关键词: 神经网络, BP算法, LDA, 预测建模