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When Will a Repost Cascade Settle Down?

  • Chi ChenEmail author
  • HongLiang Tian
  • Jie Tang
  • ChunXiao Xing
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10569)

Abstract

Repost cascades play a critical role in information diffusion on social media sites. They are developed by series of reposts and stop eventually. Substantial previous work has studied and predicted various aspects of repost cascades such as growth, burst and recur. However, how or even whether it is possible to predict when a repost cascade will settle down remains to be an open problem. Existing models cannot be directly applied to solve the problem as the feature based models are sensitive to features, while the point process based models assume that the followers of all reposters are disjoint. In this paper, we propose a novel definition settling time to model this problem. We develop a point process based model to get rid of the restriction in previous studies and make an accurate prediction of the settling time. We conduct an extensive set of experiments on Sina Weibo dataset. The results show that our model achieves over 10% performance gain than the state-of-the-art approaches after observing the cascades for 24 h.

Keywords

Repost cascade Point process Prediction 

Notes

Acknowledgment

This work was supported by NSFC (91646202), the National High-tech R&D Program of China (SS2015AA020102), Research/Project 2017YB142 supported by Ministry of Education of The People’s Republic of China Research Center for Online Education Qtone Education Group Online Education Fund, the 1000-Talent program, Tsinghua University Initiative Scientific Research Program.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Chi Chen
    • 1
    Email author
  • HongLiang Tian
    • 1
  • Jie Tang
    • 1
  • ChunXiao Xing
    • 1
  1. 1.Research Institute of Information Technology, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and TechnologyTsinghua UniversityBeijingChina

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