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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 Liu
With 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 LNAI

Series

Lecture Notes in Artificial Intelligence (LNAI)

Pagination

459 - 470

Publisher

Springer Cham

Location

Hangzhou, China

Place of publication

Cham, Switzerland

Start date

2020-08-28

End date

2020-08-30

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9783030551292

Language

eng

Publication classification

E1 Full written paper - refereed

Copyright notice

2020, Springer Nature Switzerland AG

Editor/Contributor(s)

Gang Li, Heng Shen, Ye Yuan, Xiaoyang Wang, Huawen Liu, Xiang Zhao

Title of proceedings

KSEM 2020 : Proceedings of Part 1 of the 13th International Conference on Knowledge Science, Engineering and Management

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