A Retweet Number Prediction Model Based on Followers´ Retweet Intention and Influence

Micro-blog has become the most popular information sharing tool in our daily life. The retweet behavior is a main method of information propagation in micro-blog. So there tweet number prediction not only is an interesting research topic, but also has much practical significance. However, most of current researches only regard this problem as a classification or regression problem, and they did not consider the retweet propagation process. In this paper, considering the retweet propagation process, we propose a retweet number prediction model BCI. In our model, we think retweet messages are from two parts, direct followers and indirect followers. Moreover, the retweet number of followers is decided by their retweet intention and influence. We use behavior and content information to estimate retweet intention for a direct follower and use the influence to estimate the indirect followers´ retweet number. Experimental results on Sina Weibo dataset show that our retweet number prediction model has much better performance than other well-established methods.