International journal of advanced smart convergence

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
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Identification Systems of Fake News Contents on Artificial Intelligence & Bigdata

  • KANG, Jangmook (Dept. of Hacking & Security, Far East Univ.) ;
  • LEE, Sangwon (Dept. of Computer & Software Engineering, Wonkwang Univ.)
  • Received : 2021.07.25
  • Accepted : 2021.07.29
  • Published : 2021.09.30
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Abstract

This study is about an Artificial Intelligence-based fake news identification system and its methods to determine the authenticity of content distributed over the Internet. Among the news we encounter is news that an individual or organization intentionally writes something that is not true to achieve a particular purpose, so-called fake news. In this study, we intend to design a system that uses Artificial Intelligence techniques to identify fake content that exists within the news. The proposed identification model will propose a method of extracting multiple unit factors from the target content. Through this, attempts will be made to classify unit factors into different types. In addition, the design of the preprocessing process will be carried out to parse only the necessary information by analyzing the unit factor. Based on these results, we will design the part where the unit fact is analyzed using the deep learning prediction model as a predetermined unit. The model will also include a design for a database that determines the degree of fake news in the target content and stores the information in the identified unit factor through the analyzed unit factor.

Keywords

Acknowledgement

This paper was supported by Wonkwang University in 2020.

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