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Incorporating User Grouping into Retweeting Behavior Modeling

  • Jinhai Zhu
  • Shuai Ma
  • Hui Zhang
  • Chunming Hu
  • Xiong Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10827)

Abstract

The variety among massive users makes it difficult to model their retweeting activities. Obviously, it is not suitable to cover the overall users by a single model. Meanwhile, building one model per user is not practical. To this end, this paper presents a novel solution, of which the principle is to model the retweeting behavior over user groups. Our system, GruBa, consists of three key components for extracting user based features, clustering users into groups, and modeling upon each group. Particularly, we look into the user interest from different perspectives including long-term/short-term interests and explicit/implicit interests. We have evaluated the performance of GruBa using datasets of real-world social networking applications, showcasing its benefits.

Keywords

User grouping Social networks Behavior modeling 

Notes

Acknowledgments

Ma is supported in part by NSFC U1636210, 973 Program 2014CB340300, NSFC 61421003, and MSRA Collaborative Research Program. Li is supported in part by NSFC U1636123 & 61403090. For any correspondence, please refer to Shuai Ma.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Jinhai Zhu
    • 1
    • 2
  • Shuai Ma
    • 1
    • 2
  • Hui Zhang
    • 1
    • 2
  • Chunming Hu
    • 1
    • 2
  • Xiong Li
    • 3
  1. 1.SKLSDE LabBeihang UniversityBeijingChina
  2. 2.Beijing Advanced Innovation Center for Big Data and Brain ComputingBeijingChina
  3. 3.National Computer Network Emergency Response Technical Team/Coordination Center of ChinaBeijingChina

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