COMBINING CROWD AND MACHINE INTELLIGENCE TO DETECT FALSE NEWS ON SOCIAL MEDIA
Wei, Xuan1; Zhang, Zhu2; Zhang, Mingyue3; Chen, Weiyun4; Zeng, Daniel Dajun2,5,6
Source PublicationMIS QUARTERLY
ISSN0276-7783
2022-06-01
Volume46Issue:2Pages:977-1008
Corresponding AuthorZhang, Zhu(zhu.zhang@ia.ac.cn) ; Zhang, Mingyue(zhangmy@shisu.edu.cn)
AbstractThe 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.
KeywordFalse news fake news wisdom of crowds hybrid intelligence graphical model
DOI10.25300/MISQ/2022/16526
WOS KeywordQUALITY
Indexed BySCI
Language英语
Funding ProjectNational 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]
Funding OrganizationNational 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 Research AreaComputer Science ; Information Science & Library Science ; Business & Economics
WOS SubjectComputer Science, Information Systems ; Information Science & Library Science ; Management
WOS IDWOS:000805984600010
PublisherSOC INFORM MANAGE-MIS RES CENT
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/49582
Collection复杂系统管理与控制国家重点实验室_互联网大数据与信息安全
Corresponding AuthorZhang, Zhu; Zhang, Mingyue
Affiliation1.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
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
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.
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