Micro-blog user behavior prediction aims to study user behavior habits. This paper mainly studies the factors that affect the behaviors of users of microblogging from three aspects: the user attribute, user interest, and user's emotion. We extract the characteristics of the user behaviors, training and forecasting the model. The experimental results show that the average accuracy of forwarding behavior can reach 82.56% in the prediction, the average prediction accuracy of behavior in the comments reaching 84.59%, the prediction average accuracy of likes behavior rate reaching 79.35%, which indicates the effectiveness of user interest and emotion characteristics in the promotion of microblogging user behavior prediction.