DUAL

a deep unified attention model with latent relation representations for fake news detection

Manqing Dong*, Lina Yao, Xianzhi Wang, Boualem Benatallah, Quan Z. Sheng, Hao Huang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

7 Citations (Scopus)

Abstract

The prevalence of online social media has enabled news to spread wider and faster than traditional publication channels. The easiness of creating and spreading the news, however, has also facilitated the massive generation and dissemination of fake news. It, therefore, becomes especially important to detect fake news so as to minimize its adverse impact such as misleading people. Despite active efforts to address this issue, most existing works focus on mining news’ content or context information from individuals but neglect the use of clues from multiple resources. In this paper, we consider clues from both news’ content and side information and propose a hybrid attention model to leverage these clues. In particular, we use an attention-based bi-directional Gated Recurrent Units (GRU) to extract features from news content and a deep model to extract hidden representations of the side information. We combine the two hidden vectors resulted from the above extractions into an attention matrix and learn an attention distribution over the vectors. Finally, the distribution is used to facilitate better fake news detection. Our experimental results on two real-world benchmark datasets show our approach outperforms multiple baselines in the accuracy of detecting fake news.

Original languageEnglish
Title of host publicationWeb Information Systems Engineering – WISE 2018
Subtitle of host publication19th International Conference, 2018, Proceedings, Part I
EditorsHakim Hacid, Wojciech Cellary, Hua Wang, Hye-Young Paik, Rui Zhou
Place of PublicationCham
PublisherSpringer-VDI-Verlag GmbH & Co. KG
Pages199-209
Number of pages11
ISBN (Electronic)9783030029227
ISBN (Print)9783030029210
DOIs
Publication statusPublished - 1 Jan 2018
Event19th International Conference on Web Information Systems Engineering, WISE 2018 - Dubai, United Arab Emirates
Duration: 12 Nov 201815 Nov 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11233 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th International Conference on Web Information Systems Engineering, WISE 2018
CountryUnited Arab Emirates
CityDubai
Period12/11/1815/11/18

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