Abstract:With the rapid development of the Internet, the Weibo has gradually become an important way of information dissemination and information collection in social communication, and Weibo retweeting is an important way to spread information on Weibo.The study of the Weibo retweeting problem has a very important significance to Weibo communication, Weibo marketing, and public opinion monitoring. The main factors affecting the retweeting of Weibo are similarity between followers' interest and Weibo text, and changes in Weibo marketing strategy and number of user followers. The previous forecasting models did not consider these two factors comprehensively. To solve the above mentioned problem, this study proposes a method based on recurrent neural network to predict magnitude of Weibo retweeting. First, the SIM-LSTM model is used to build the trend of Weibo retweeting. Then, TF-IDF is used to build the similarity between followers' interest and Weibo text. And finally, neural network model is used to predict whether followers will forward the Weibo. the experiments show that the F1 evaluation value using the proposed algorithm is increased by 5% comparing with other traditional prediction methods.