Provenance-Based Rumor Detection

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Author(s)
Chi, Thang Duong
Quoc, Viet Hung Nguyen
Wang, Sen
Stantic, Bela
Year published
2017
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With the advance of social media networks, people are sharing contents in an unprecedented scale. This makes social networks such as microblogs an ideal place for spreading rumors. Although different types of information are available in a post on social media, traditional approaches in rumor detection leverage only the text of the post, which limits their accuracy in detection. In this paper, we propose a provenance-aware approach based on recurrent neural network to combine the provenance information and the text of the post itself to improve the accuracy of rumor detection. Experimental results on a real-world dataset ...
View more >With the advance of social media networks, people are sharing contents in an unprecedented scale. This makes social networks such as microblogs an ideal place for spreading rumors. Although different types of information are available in a post on social media, traditional approaches in rumor detection leverage only the text of the post, which limits their accuracy in detection. In this paper, we propose a provenance-aware approach based on recurrent neural network to combine the provenance information and the text of the post itself to improve the accuracy of rumor detection. Experimental results on a real-world dataset show that our technique is able to outperform state-of-the-art approaches in rumor detection.
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View more >With the advance of social media networks, people are sharing contents in an unprecedented scale. This makes social networks such as microblogs an ideal place for spreading rumors. Although different types of information are available in a post on social media, traditional approaches in rumor detection leverage only the text of the post, which limits their accuracy in detection. In this paper, we propose a provenance-aware approach based on recurrent neural network to combine the provenance information and the text of the post itself to improve the accuracy of rumor detection. Experimental results on a real-world dataset show that our technique is able to outperform state-of-the-art approaches in rumor detection.
View less >
Journal Title
Lecture Notes in Computer Science
Volume
10538
Copyright Statement
© 2017 Springer International Publishing AG. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. The original publication is available at www.springerlink.com.
Subject
Database systems
Information and computing sciences