Predicting the popularity of messages based on big data

Social media has been an important way for people to get news. It is designed to make the sharing of messages very fast and easy. It also attracted the attention of a large number of researchers. There has been research concerning predicting what messages will be popular. But it lacks of in-depth study of what features play an important role in the prediction task. In the work, we systematically and comprehensively study three types of features: user features, text features and time features. Multiple comparison experiments are carried out on big data platform. Experimental results show that time features are the most valuable features, almost close to the effect of all the features, and the popularity of messages is predicted with a satisfactory accuracy.