Fake News Types and Detection Models on Social Media A State-of-the-Art Survey

  • Botambu Collins
  • Dinh Tuyen Hoang
  • Ngoc Thanh Nguyen
  • Dosam HwangEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1178)


Fake news has gained prominence since the 2016 US presidential election as well as the Brexit referendum. Fake news has abused not only the press but also the democratic rules. Therefore, the need to restrict and eliminate it becomes inevitable. The popularity of fake news on social media has made people unwilling to engage in sharing positive news for fear that the information is false. The main problem with fake news is how quickly it spreads to social media.

In this paper, we introduced an overview of the various models in detecting fake news such as Machine learning, Natural Language Processing, Crowd-sourced techniques, Expert fact-checker, as well as Hybrid Expert-Machine. We also do reviews of different types of fake news, which is an essential criterion for detecting fake news. Our findings show that detecting fake news is a challenging but workable task. The techniques that combine people and machines bring very satisfactory results. We also study about open issues of fake news, then propose some potential research tasks for future works.


Fake news Fake news detection Deception detection 



This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2017R1A2B4009410), and the National Research Foundation of Korea (NRF) grant funded by the BK21PLUS Program (22A20130012009).


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Botambu Collins
    • 1
  • Dinh Tuyen Hoang
    • 1
    • 3
  • Ngoc Thanh Nguyen
    • 2
  • Dosam Hwang
    • 1
    Email author
  1. 1.Department of Computer EngineeringYeungnam UniversityGyeongsan-siSouth Korea
  2. 2.Faculty of Computer Science and ManagementWroclaw University of Science and TechnologyWroclawPoland
  3. 3.Faculty of Engineering and Information TechnologyQuang Binh UniversityĐồng HớiVietnam

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