Abstract
How fake news goes viral via social media? How does its propagation pattern differ from real stories? In this paper, we attempt to address the problem of identifying rumors, i.e., fake information, out of microblog posts based on their propagation structure. We firstly model microblog posts diffusion with propagation trees, which provide valuable clues on how an original message is transmitted and developed over time. We then propose a kernel-based method called Propagation Tree Kernel, which captures high-order patterns differentiating different types of rumors by evaluating the similarities between their propagation tree structures. Experimental results on two real-world datasets demonstrate that the proposed kernel-based approach can detect rumors more quickly and accurately than state-ofthe-art rumor detection models.
Original language | English |
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Title of host publication | ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers) |
Publisher | Association for Computational Linguistics (ACL) |
Pages | 708-717 |
Number of pages | 10 |
Volume | 1 |
ISBN (Electronic) | 9781945626753 |
DOIs | |
Publication status | Published - 1 Jan 2017 |
Event | 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017 - Vancouver, Canada Duration: 30 Jul 2017 → 4 Aug 2017 |
Other
Other | 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017 |
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Country | Canada |
City | Vancouver |
Period | 30/7/17 → 4/8/17 |
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ASJC Scopus subject areas
- Language and Linguistics
- Artificial Intelligence
- Software
- Linguistics and Language
Cite this
Detect rumors in microblog posts using propagation structure via kernel learning. / Ma, Jing; Gao, Wei; Wong, Kam Fai.
ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers). Vol. 1 Association for Computational Linguistics (ACL), 2017. p. 708-717.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Detect rumors in microblog posts using propagation structure via kernel learning
AU - Ma, Jing
AU - Gao, Wei
AU - Wong, Kam Fai
PY - 2017/1/1
Y1 - 2017/1/1
N2 - How fake news goes viral via social media? How does its propagation pattern differ from real stories? In this paper, we attempt to address the problem of identifying rumors, i.e., fake information, out of microblog posts based on their propagation structure. We firstly model microblog posts diffusion with propagation trees, which provide valuable clues on how an original message is transmitted and developed over time. We then propose a kernel-based method called Propagation Tree Kernel, which captures high-order patterns differentiating different types of rumors by evaluating the similarities between their propagation tree structures. Experimental results on two real-world datasets demonstrate that the proposed kernel-based approach can detect rumors more quickly and accurately than state-ofthe-art rumor detection models.
AB - How fake news goes viral via social media? How does its propagation pattern differ from real stories? In this paper, we attempt to address the problem of identifying rumors, i.e., fake information, out of microblog posts based on their propagation structure. We firstly model microblog posts diffusion with propagation trees, which provide valuable clues on how an original message is transmitted and developed over time. We then propose a kernel-based method called Propagation Tree Kernel, which captures high-order patterns differentiating different types of rumors by evaluating the similarities between their propagation tree structures. Experimental results on two real-world datasets demonstrate that the proposed kernel-based approach can detect rumors more quickly and accurately than state-ofthe-art rumor detection models.
UR - http://www.scopus.com/inward/record.url?scp=85040238063&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85040238063&partnerID=8YFLogxK
U2 - 10.18653/v1/P17-1066
DO - 10.18653/v1/P17-1066
M3 - Conference contribution
AN - SCOPUS:85040238063
VL - 1
SP - 708
EP - 717
BT - ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers)
PB - Association for Computational Linguistics (ACL)
ER -