Abstract
Rumor detection is a very challenging and urgent issue. Text is the most fundamental and significant owing to its high usability and accessibility. In this paper, we propose a fusion neural network based on the text for rumor detection, which is called Text-based Fusion Neural Network (T-FNN). For accurately extracting contextual features, we present a new data processing algorithm, and construct a fusion neural network including bi-directional gated recurrent unit, convolutional model, and attention mechanism. Experimental results on two real-life datasets show that our proposed T-FNN has much better performance than other text-based state-of-art models on rumor detection.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Ma, J., et al.: Detecting rumors from microblogs with recurrent neural networks. In: IJCAI, pp. 3818–3824 (2016)
Chen, T., Li, X., Yin, H., Zhang, J.: Call attention to rumors: deep attention based recurrent neural networks for early rumor detection. In: Ganji, M., Rashidi, L., Fung, B.C.M., Wang, C. (eds.) PAKDD 2018. LNCS (LNAI), vol. 11154, pp. 40–52. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-04503-6_4
Liu, Q., Yu, F., Wu, S., Wang, L.: Mining significant microblogs for misinformation identification: an attention-based approach. ACM Trans. Intell. Syst. Technol. (TIST) 9(5), 50 (2018)
Guo, H., Cao, J., Zhang, Y., Guo, J., Li, J.: Rumor detection with hierarchical social attention network. In: Proceedings of the 27th ACM International Conference on Information and Knowledge Management, pp. 943–951. ACM (2018)
Acknowledgment
This work is supported by The National Key Research and Development Program of China (Grant No. 2017YFB0803001) and The National Natural Science Foundation of China (Grant No. 61572459).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Chen, Y., Hu, L., Sui, J. (2019). Text-Based Fusion Neural Network for Rumor Detection. In: Douligeris, C., Karagiannis, D., Apostolou, D. (eds) Knowledge Science, Engineering and Management. KSEM 2019. Lecture Notes in Computer Science(), vol 11776. Springer, Cham. https://doi.org/10.1007/978-3-030-29563-9_11
Download citation
DOI: https://doi.org/10.1007/978-3-030-29563-9_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-29562-2
Online ISBN: 978-3-030-29563-9
eBook Packages: Computer ScienceComputer Science (R0)