@inproceedings{a1710bfa20154f748b54c984a9f9a5d5,
title = "Popularity prediction of burst event in microblogging",
abstract = "Every day, thousands of burst events are generated in microblogging first, and then affect the public opinion to a large degree. Thus, it is quite necessary to find out {"}how hot the burst event will be in the future{"}. In this paper, we propose a prediction model which combines the analysis of event content and users' interest to predict the volume of the burst event in the implicit network. Particularly, it is assumed that different user has different influence power and different interest in the burst event. The popularity of an event depends on the volumes produced by the users infected in the past and its historical popularity. Experimental results show the superior performance of our approach.",
keywords = "Burst event, Event detection, Event popularity, Information spread",
author = "Xiaoming Zhang and Zhoujun Li and Wenhan Chao and Jiali Xia",
year = "2014",
doi = "10.1007/978-3-319-08010-9\_53",
language = "英语",
isbn = "9783319080093",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "484--487",
booktitle = "Web-Age Information Management - 15th International Conference, WAIM 2014, Proceedings",
address = "德国",
note = "15th International Conference on Web-Age Information Management, WAIM 2014 ; Conference date: 16-06-2014 Through 18-06-2014",
}