Multi-Modal Meta Multi-Task Learning for Social Media Rumor Detection

doi:10.1109/TMM.2021.3065498

	Multi-Modal Meta Multi-Task Learning for Social Media Rumor Detection
	Zhang, Huaiwen1,2 ; Qian, Shengsheng1,2 ; Fang, Quan1,2 ; Xu, Changsheng1,2,3
发表期刊	IEEE TRANSACTIONS ON MULTIMEDIA
ISSN	1520-9210
	2022
卷号	24 页码:1449-1459
通讯作者	Xu, Changsheng(csxu@nlpr.ia.ac.cn)
摘要	With the rapid development of social media platforms and the increasing scale of the social media data, the rumor detection task has become vitally important since the authenticity of posts cannot be guaranteed. To date, Many approaches have been proposed to facilitate the rumor detection process by utilizing the multi-task learning mechanism, which aims to improve the performance of rumor detection task by leveraging the useful information in the stance detection task. However, most of the existing approaches suffer from three limitations: (1) only focus on the textual content and ignore the multi-modal information which is key component contained in social media data; (2) ignore the difference of feature space between the stance detection task and rumor detection task, resulting in the unsatisfactory usage of stance information; (3) largely neglect the semantic information hidden in the fine-grained stance labels. Therefore, in this paper, we design a Multi-modal Meta Multi-Task Learning (MM-MTL) framework for social media rumor detection. To make use of multiple modalities, we design a multi-modal post embedding layer which considers both textual and visual content. To overcome the feature-sharing problem of the stance detection task and rumor detection task, we propose a meta knowledge-sharing scheme to share some higher meta network-layers and capture the meta knowledge behind the multi-modal post. To better utilize the semantic information hidden in the fine-grained stance labels, we employ the attention mechanism to estimate the weight of each reply. Extensive experiments on two Twitter benchmark datasets demonstrate that our proposed method achieves state-of-the-art performance.
关键词	Task analysis Social networking (online) Feature extraction Learning systems Semantics Media Blogs Meta learning multi-modal multi-task learning rumor detection social media
DOI	10.1109/TMM.2021.3065498
收录类别	SCI
语种	英语
资助项目	National Key Research, and Development Program of China[2017YFB1002804] ; National Natural Science Foundation of China[62036012] ; National Natural Science Foundation of China[61721004] ; National Natural Science Foundation of China[61720106006] ; National Natural Science Foundation of China[61802405] ; National Natural Science Foundation of China[62072456] ; National Natural Science Foundation of China[61832002] ; National Natural Science Foundation of China[61936005] ; National Natural Science Foundation of China[U1705262] ; Key Research Program of Frontier Sciences, CAS[QYZDJSSWJSC039] ; Open Research Projects of Zhejiang Laboratory[2021KE0AB05] ; K.C. Wong Education Foundation ; CCF-Tencent Open Fund
项目资助者	National Key Research, and Development Program of China ; National Natural Science Foundation of China ; Key Research Program of Frontier Sciences, CAS ; Open Research Projects of Zhejiang Laboratory ; K.C. Wong Education Foundation ; CCF-Tencent Open Fund
WOS研究方向	Computer Science ; Telecommunications
WOS类目	Computer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS记录号	WOS:000776227200017
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
七大方向——子方向分类	多模态智能
引用统计	被引频次：24[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/48217
专题	多模态人工智能系统全国重点实验室_多媒体计算
通讯作者	Xu, Changsheng
作者单位	1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Peng Cheng Lab, Shenzhen 518055, Peoples R China
第一作者单位	模式识别国家重点实验室
通讯作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Zhang, Huaiwen,Qian, Shengsheng,Fang, Quan,et al. Multi-Modal Meta Multi-Task Learning for Social Media Rumor Detection[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2022,24:1449-1459.
APA	Zhang, Huaiwen,Qian, Shengsheng,Fang, Quan,&Xu, Changsheng.(2022).Multi-Modal Meta Multi-Task Learning for Social Media Rumor Detection.IEEE TRANSACTIONS ON MULTIMEDIA,24,1449-1459.
MLA	Zhang, Huaiwen,et al."Multi-Modal Meta Multi-Task Learning for Social Media Rumor Detection".IEEE TRANSACTIONS ON MULTIMEDIA 24(2022):1449-1459.