Abstract
Retweet, as a main way to spread information in twitter, has been researched in a number of works. Recently research focuses on analyzing the factors of retweet behavior. However, the prediction on retweet behavior is a new challenge which is not well studied in the past. A basic fact is that different people are interested in different kinds of tweets, and they will retweet tweets which they are interested in. First, we collect tweets of different categories from valid account of famous news media as learning corpus. Second, in order to discover user interests, we classify user tweets into different categories by Bayes model. Finally, we measure user interests on tweets of different categories, and predict retweet behavior by interest measurement. This paper extends the previous study on retweet behavior, and we predict user retweet behavior as well as infer user interests. Experiment shows Bayes model has good performance on classifying tweets, and our algorithm achieves more precision than others.
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