Source of Publication
Procedia Computer Science
© 2018 The Authors. Published by Elsevier Ltd. 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.
Computer Sciences | Social and Behavioral Sciences
Classification, Clickbaits, Fake news, Social media
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Aldwairi, Monther and Alwahedi, Ali, "Detecting fake news in social media networks" (2018). All Works. 1216.
Indexed in Scopus
Open Access Type
Gold: This publication is openly available in an open access journal/series