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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Main Authors: MA, Jing, GAO, Wei, WONG, Kam-Fai
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Language:English
Published: Institutional Knowledge at Singapore Management University 2017
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Online Access: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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spelling 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
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Databases and Information Systems
spellingShingle Databases and Information Systems
MA, Jing
GAO, Wei
WONG, Kam-Fai
Detect rumors in microblog posts using propagation structure via kernel learning
description 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.
format text
author MA, Jing
GAO, Wei
WONG, Kam-Fai
author_facet MA, Jing
GAO, Wei
WONG, Kam-Fai
author_sort 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
title_full_unstemmed Detect rumors in microblog posts using propagation structure via kernel learning
title_sort detect rumors in microblog posts using propagation structure via kernel learning
publisher Institutional Knowledge at Singapore Management University
publishDate 2017
url 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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