COMBINING CROWD AND MACHINE INTELLIGENCE TO DETECT FALSE NEWS ON SOCIAL MEDIA

doi:10.25300/MISQ/2022/16526

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 互联网大数据与信息安全

	COMBINING CROWD AND MACHINE INTELLIGENCE TO DETECT FALSE NEWS ON SOCIAL MEDIA
	Wei, Xuan 1; Zhang, Zhu2 ; Zhang, Mingyue 3; Chen, Weiyun 4; Zeng, Daniel Dajun2,5,6
发表期刊	MIS QUARTERLY
ISSN	0276-7783
	2022-06-01
卷号	46 期号:2 页码:977-1008
通讯作者	Zhang, Zhu(zhu.zhang@ia.ac.cn) ; Zhang, Mingyue(zhangmy@shisu.edu.cn)
摘要	The explosive spread of false news on social media has severely affected many areas such as news ecosystems, politics, economics, and public trust, especially amid the COVID-19 infodemic. Machine intelligence has met with limited success in detecting and curbing false news. Human knowledge and intelligence hold great potential to complement machine-based methods. Yet they are largely underexplored in current false news detection research, especially in terms of how to efficiently utilize such information. We observe that the crowd contributes to the challenging task of assessing the veracity of news by posting responses or reporting. We propose combining these two types of scalable crowd judgments with machine intelligence to tackle the false news crisis. Specifically, we design a novel framework called CAND, which first extracts relevant human and machine judgments from data sources including news features and scalable crowd intelligence. The extracted information is then aggregated by an unsupervised Bayesian aggregation model. Evaluation based on Weibo and Twitter datasets demonstrates the effectiveness of crowd intelligence and the superior performance of the proposed framework in comparison with the benchmark methods. The results also generate many valuable insights, such as the complementary value of human and machine intelligence, the possibility of using human intelligence for early detection, and the robustness of our approach to intentional manipulation. This research significantly contributes to relevant literature on false news detection and crowd intelligence. In practice, our proposed framework serves as a feasible and effective approach for false news detection.
关键词	False news fake news wisdom of crowds hybrid intelligence graphical model
DOI	10.25300/MISQ/2022/16526
关键词[WOS]	QUALITY
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2020AAA0103405] ; National Natural Science Foundation of China[71621002] ; National Natural Science Foundation of China[71802024] ; National Natural Science Foundation of China[62071467] ; National Natural Science Foundation of China[72192822] ; National Natural Science Foundation of China[71974187] ; Shanghai Chenguang Program[21CGA13] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDA27030100] ; Innovative Research Team of Shanghai International Studies University[2020114044]
项目资助者	National Key Research and Development Program of China ; National Natural Science Foundation of China ; Shanghai Chenguang Program ; Strategic Priority Research Program of Chinese Academy of Sciences ; Innovative Research Team of Shanghai International Studies University
WOS研究方向	Computer Science ; Information Science & Library Science ; Business & Economics
WOS类目	Computer Science, Information Systems ; Information Science & Library Science ; Management
WOS记录号	WOS:000805984600010
出版者	SOC INFORM MANAGE-MIS RES CENT
引用统计	被引频次：9[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/173211/49582
专题	多模态人工智能系统全国重点实验室_互联网大数据与信息安全
通讯作者	Zhang, Zhu; Zhang, Mingyue
作者单位	1.Shanghai Jiao Tong Univ, Antai Coll Econ & Management, Shanghai, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China 3.Shanghai Int Studies Univ, Sch Business & Management, Shanghai, Peoples R China 4.Huazhong Univ Sci & Technol, Sch Management, Wuhan, Peoples R China 5.Univ Chinese Acad Sci, Sch Econ & Management, Beijing, Peoples R China 6.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Wei, Xuan,Zhang, Zhu,Zhang, Mingyue,et al. COMBINING CROWD AND MACHINE INTELLIGENCE TO DETECT FALSE NEWS ON SOCIAL MEDIA[J]. MIS QUARTERLY,2022,46(2):977-1008.
APA	Wei, Xuan,Zhang, Zhu,Zhang, Mingyue,Chen, Weiyun,&Zeng, Daniel Dajun.(2022).COMBINING CROWD AND MACHINE INTELLIGENCE TO DETECT FALSE NEWS ON SOCIAL MEDIA.MIS QUARTERLY,46(2),977-1008.
MLA	Wei, Xuan,et al."COMBINING CROWD AND MACHINE INTELLIGENCE TO DETECT FALSE NEWS ON SOCIAL MEDIA".MIS QUARTERLY 46.2(2022):977-1008.