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Asia Information Retrieval Symposium

AIRS 2019: Information Retrieval Technology pp 173–184Cite as

Detecting Emerging Rumors by Embedding Propagation Graphs

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12004))

Abstract

In this paper, we propose a propagation-driven approach to discover newly emerging rumors which are spreading on social media. Firstly, posts and their responsive ones (i.e., comments, sharing) are modeled as graphs. These graphs will be embedded using their structure and node’s attributes. We then train a classifier to predict from these graph embedding vectors rumor labels. In addition, we also propose an incremental training method to learn embedding vectors of out-of-vocabulary (OOV) words because newly emerging rumor regularly contains new terminologies. To demonstrate the actual performance, we conduct an experiment by using a real-world dataset which is collected from Twitter. The result shows that our approach outperforms the state-of-the-art method with a large margin.

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Acknowledgments

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (2017R1A2B4010774, 2017R1A4A1015675).

Author information

Authors and Affiliations

  1. Department of Computer Engineering, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul, Korea

    Dang-Thinh Vu & Jason J. Jung

Authors
  1. Dang-Thinh Vu
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  2. Jason J. Jung
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Corresponding author

Correspondence to Jason J. Jung .

Editor information

Editors and Affiliations

  1. Open University of Hong Kong, Hong Kong, China

    Fu Lee Wang

  2. The Education University of Hong Kong, Hong Kong, China

    Haoran Xie

  3. Chinese University of Hong Kong, Hong Kong, China

    Wai Lam

  4. Nanyang Technological University, Singapore, Singapore

    Aixin Sun

  5. Institute of Information Science, Academia Sinica, Taipei, Taiwan

    Lun-Wei Ku

  6. South China Normal University, Guangzhou, China

    Tianyong Hao

  7. Chinese Academy of Agricultural Sciences, Beijing, China

    Wei Chen

  8. Douglas College, New Westminster, BC, Canada

    Tak-Lam Wong

  9. University of Southern Queensland, Toowoomba, QLD, Australia

    Xiaohui Tao

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Cite this paper

Vu, DT., Jung, J.J. (2020). Detecting Emerging Rumors by Embedding Propagation Graphs. In: Wang, F., et al. Information Retrieval Technology. AIRS 2019. Lecture Notes in Computer Science(), vol 12004. Springer, Cham. https://doi.org/10.1007/978-3-030-42835-8_15

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  • DOI: https://doi.org/10.1007/978-3-030-42835-8_15

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-42834-1

  • Online ISBN: 978-3-030-42835-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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