An analysis of influential users for predicting the popularity of news tweets

Abstract

Twitter plays an important role in today social network. Its key mechanism is retweet that disseminates information to broad audiences within a very short time and help increases the popularity of the social content. Therefore, an effective model for predicting the popularity of tweets is required in various domains such as news propagation, viral marketing, personalized message recommendation, and trend analysis. Although many studies have been extensively researched on predicting the popularity of tweets, they mainly focus on the content-based and the author-based features, while retweeter-based features are less concerned. This paper aims to study the impact of influential users who retweet tweets, also called retweeters, and presents simple yet effective measures for predicting the influence of retweeters on the popularity of online news tweets. By analyzing the popularity of news tweets and the impact of the retweeters, a number of useful measures are defined to evaluate influence of users in the retweeter network, and used to establish the prediction model. The experimental results show that the application of the retweeter-based features is highly effective and enhances the performance of the prediction model with high accuracy.