Research on the Prediction of Popular Opinion Trend of Web News based on BP neural Network and LSTM

Abstract

Abstract Current prediction methods on public opinion trend of network news are often carried out according to human experience or traditional time series prediction, but they sometimes lack scientific principle and immediacy. This paper researches on the prediction of public opinion trend of network news based on deep learning. Firstly, we use the BP neural network and LSTM to predict public sentiment trend, then combine word2vec with LSTM to classify the text sentiment and finally use doc2vec algorithm and k-means to cluster the text. Experiment result shows that the mean square error with good performance, which reveals the beneficial effect of our prediction method.