Detecting Fake News in Social Media Networks

被引:107
作者
Aldwairi, Monther [1 ]
Alwahedi, Ali [1 ]
机构
[1] Zayed Univ, Coll Technol Innovat, Abu Dhabi 144534, U Arab Emirates
来源
9TH INTERNATIONAL CONFERENCE ON EMERGING UBIQUITOUS SYSTEMS AND PERVASIVE NETWORKS (EUSPN-2018) / 8TH INTERNATIONAL CONFERENCE ON CURRENT AND FUTURE TRENDS OF INFORMATION AND COMMUNICATION TECHNOLOGIES IN HEALTHCARE (ICTH-2018) | 2018年 / 141卷
关键词
Fake news; clickbaits; social media; classification;
D O I
10.1016/j.procs.2018.10.171
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Fake news and hoaxes have been there since before the advent of the Internet. The widely accepted definition of Internet fake news is: fictitious articles deliberately fabricated to deceive readers". Social media and news outlets publish fake news to increase readership or as part of psychological warfare. Ingeneral, the goal is profiting through clickbaits. Clickbaits lure users and entice curiosity with flashy headlines or designs to click links to increase advertisements revenues. This exposition analyzes the prevalence of fake news in light of the advances in communication made possible by the emergence of social networking sites. The purpose of the work is to come up with a solution that can be utilized by users to detect and filter out sites containing false and misleading information. We use simple and carefully selected features of the title and post to accurately identify fake posts. The experimental results show a 99.4% accuracy using logistic classifier. (C) 2018 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:215 / 222
页数:8
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