On Burst Detection and Prediction in Retweeting Sequence

Message propagation via retweet chain can be regarded as a social contagion process. In this paper, we examine burst patterns in retweet activities. A burst is a large number of retweets of a particular tweet occurring within a certain short time window. The occurring of a burst indicates the original tweet receives abnormally high attentions during the burst period. It will be imperative to characterize burst patterns and develop algorithms to detect and predict bursts. We propose the use of the Cantelli’s inequality to identify bursts from retweet sequence data. We conduct a comprehensive empirical analysis of a large microblogging dataset collected from the Sina Weibo and report our observations of burst patterns. Based on our empirical findings, we extract various features from users’ profiles, followship topology, and message topics and investigate whether and how accurate we can predict bursts using classifiers based on the extracted features. Our empirical study of the Si...

• Type: Journal
• Year: 2015
• Where: PAKDD
• Authors: Zhilin Luo, Yue Wang 0009, Xintao Wu, Wandong Cai, Ting Chen
• Keywords: Data Mining, PAKDD 2015