Detect rumors in microblog posts using propagation structure via kernel learning
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 diffusio...
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sg-smu-ink.sis_research-55662020-02-27T02:15:21Z Detect rumors in microblog posts using propagation structure via kernel learning MA, Jing GAO, Wei WONG, Kam-Fai 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. 2017-08-04T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/4563 info:doi/10.18653/v1/P17-1066 https://ink.library.smu.edu.sg/context/sis_research/article/5566/viewcontent/P17_1066.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Databases and Information Systems |
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Databases and Information Systems MA, Jing GAO, Wei WONG, Kam-Fai Detect rumors in microblog posts using propagation structure via kernel learning |
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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. |
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MA, Jing GAO, Wei WONG, Kam-Fai |
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MA, Jing GAO, Wei WONG, Kam-Fai |
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MA, Jing |
title |
Detect rumors in microblog posts using propagation structure via kernel learning |
title_short |
Detect rumors in microblog posts using propagation structure via kernel learning |
title_full |
Detect rumors in microblog posts using propagation structure via kernel learning |
title_fullStr |
Detect rumors in microblog posts using propagation structure via kernel learning |
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Detect rumors in microblog posts using propagation structure via kernel learning |
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detect rumors in microblog posts using propagation structure via kernel learning |
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Institutional Knowledge at Singapore Management University |
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2017 |
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https://ink.library.smu.edu.sg/sis_research/4563 https://ink.library.smu.edu.sg/context/sis_research/article/5566/viewcontent/P17_1066.pdf |
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