Prediction of user's retweet behavior in social network

Based on the tweet's topic and user's characteristics on Sina Weibo, a prediction algorithm for user's retweet behavior in social network was proposed. Firstly, use mutual information theory to extract features from retweeted users' tweet content. Compute the relevance between extracted features and given user's tweet content to predict the user's retweet behavior. Then study the relationship between user's retweet behavior and user's other characteristics such as gender, number of friends, number of followers, and number of tweets to select proper user characterization. Use user characterization and Bayesian model to predict a given user's retweet probability. Combining the results from the above two methods to make a final prediction of user's retweet behavior on a tweet with given topic. The prediction algorithm is of great significance in studying the spread of internet public opinion and microblogging marketing.