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Predicting user influence in the propagation of toxic information
conference contribution
posted on 2020-01-01, 00:00 authored by Shu Li, Yishuo Zhang, Penghui Jiang, Zhao Li, Chris ZhangChris Zhang, Qingyun LiuWith the advances of information technology, the Internet has become an indispensable part of life. At the same time, toxic Information has become virulent and common on the Internet. Such information propagation can have a negative impact on individuals, organisations and the society. Traditional approaches, such as detecting texts and posts with toxic Information will eventually generate ‘dark pools in which the online propagation of toxic information will flourish. In this study, we pay attention to influential users who evidently affect others in the activities related to toxic information. A method of predicting user influence was proposed. Compared to the existing literature, user influence is assessed on the basis of users’ text-based and behaviors-based characteristics rather than the network structures only. Moreover, whether the influential users have always been those with strong connections on the social networking site is also discussed. The effectiveness of the proposed method is demonstrated in two real-world datasets.
History
Event
KSEM Knowledge Science, Engineering and Management. International Conference (13th : 2020 : Hangzhou, China)Volume
12274 LNAISeries
Lecture Notes in Artificial Intelligence (LNAI)Pagination
459 - 470Publisher
Springer ChamLocation
Hangzhou, ChinaPlace of publication
Cham, SwitzerlandPublisher DOI
Start date
2020-08-28End date
2020-08-30ISSN
0302-9743eISSN
1611-3349ISBN-13
9783030551292Language
engPublication classification
E1 Full written paper - refereedCopyright notice
2020, Springer Nature Switzerland AGEditor/Contributor(s)
Gang Li, Heng Shen, Ye Yuan, Xiaoyang Wang, Huawen Liu, Xiang ZhaoTitle of proceedings
KSEM 2020 : Proceedings of Part 1 of the 13th International Conference on Knowledge Science, Engineering and ManagementUsage metrics
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