Fake News Detection Techniques: A Survey

Document Type : Original Article

Authors

1 Information System Department, Faculty of Computers and ArtificialIntelligence, Helwan University

2 Faculty of Informatics and Computer Science, British University in Egypt, Cairo, Egypt

Abstract

With the spread of smartphones and the use of social communication networks with different groups of people, fake news has been spread to gain some interactions or any other intentions. Unfortunately, people trust social media platforms and believe most in their news even if it is impossible so we can say that any news of any type will find their audience or believers. People’s trust and beliefs translated into actions, so fake news can lead to problems that may affect the economy, politics, or panic at the individual level. Organizations with malicious intents exploit this point which can be described as a lake of consciousness to perform their goals which can be beating another competitive organization or destroying a country and displacing innocent people. Recently, many studies have shown wide interest in the process of classifying false news. The classification of fake news falls under the classification of texts and is a sub-task of understanding natural language. In this paper, a reference survey is provided for all the methods and methodologies that have been used by researchers to discover fake news that spread through social network sites. The used datasets, classification techniques, models, and results are discussed.

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