Human-machine interaction: A case study on fake news detection using a backtracking based on a cognitive system

被引：21

作者：

Ko, Hoon ^{[1
]}

Hong, Jong Youl ^{[2
]}

Kim, Sangheon ^{[3
]}

Mesicek, Libor ^{[4
]}

Na, In Seop ^{[5
]}

机构：

[1] Chosun Univ, IT Res Inst, Gwangju, South Korea

[2] Hankuk Univ Foreign Studies, Seoul, South Korea

[3] Sangmyung Univ, Dept Hist & Hist Content, Seoul, South Korea

[4] Univ JE Purkyne, Moskevska 54, Usti Nad Labem 40096, Czech Republic

[5] Chosun Univ, Software Convergence Educ Inst, Gwangju, South Korea

来源：

COGNITIVE SYSTEMS RESEARCH | 2019年 / 55卷

关键词：

Reverse-tracking; Cognitive system; Fake news; PageRank;

D O I：

10.1016/j.cogsys.2018.12.018

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Although the Internet provides a variety of news, it also can give confusion caused by personal subjective thoughts such as personal TV, blogs, and unproven news. The unproven news is written in a subjective direction with added personal opinions rather than objective content, so readers may acquire knowledge with the wrong outlook. In addition, fake news is being produced and the problem of social polarization is becoming serious. In the end, it is necessary to detect the fake news, but it is not easy to distinguish the truth of published news because of the lack of fake news distinction time compared to the speed of information sharing on the Internet and the diversity and strong subjectivity of news. Therefore, in this paper, the possibility of fake news is defined by using the reverse-tracking method of the articles which are posted on the Cognitive System. Finally, as the result, the detection rate is average 85%. (C) 2018 Elsevier B.V. All rights reserved.

引用

页码：77 / 81

页数：5

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