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Fake News Detection on Social Networks with Artificial Intelligence Tools: Systematic Literature Review

  • Murat Goksu
  • Nadire CavusEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1095)

Abstract

Rapid advances in technology have enabled print media to be published online and the emergence of Facebook, Twitter, YouTube and other social networks. Social networks have become an important way for people to communicate with each other and share their ideas. The most important feature of social networks is the rapid information sharing. In this context, the accuracy of the news or information published is very important. The spread of fake news in social networks has recently become one of the biggest problems. Fake news affects people’s daily life and social order and may cause some negativity. In this study, the most comprehensive and prestigious electronic databases have been examined in order to find the latest articles about the detection of fake news in social networks by systematic literature review method. The main aim of the study is to reveal the benefits of artificial intelligence tools used in the detection of fake news and their success levels in different applications. As a result of the study, it was concluded that the success levels of artificial intelligence tools are over 90%. This study is thought to be a guide both researchers and individuals related to this field.

Keywords

Fake news detection Social networks Artificial intelligence 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Computer Information SystemsNear East UniversityNicosiaTurkey

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