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

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Intelligent Information and Database Systems (ACIIDS 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1178))

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Abstract

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.

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Acknowledgment

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).

Author information

Authors and Affiliations

  1. Department of Computer Engineering, Yeungnam University, Gyeongsan-si, South Korea

    Botambu Collins, Dinh Tuyen Hoang & Dosam Hwang

  2. Faculty of Computer Science and Management, Wroclaw University of Science and Technology, Wroclaw, Poland

    Ngoc Thanh Nguyen

  3. Faculty of Engineering and Information Technology, Quang Binh University, Đồng Hới, Vietnam

    Dinh Tuyen Hoang

Authors
  1. Botambu Collins
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  2. Dinh Tuyen Hoang
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  3. Ngoc Thanh Nguyen
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  4. Dosam Hwang
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Corresponding author

Correspondence to Dosam Hwang .

Editor information

Editors and Affiliations

  1. Kielce University of Technology, Kielce, Poland

    Paweł Sitek

  2. Wrocław University of Science and Technology, Wrocław, Poland

    Marcin Pietranik

  3. Wrocław University of Science and Technology, Wrocław, Poland

    Marek Krótkiewicz

  4. King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand

    Chutimet Srinilta

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Collins, B., Hoang, D.T., Nguyen, N.T., Hwang, D. (2020). Fake News Types and Detection Models on Social Media A State-of-the-Art Survey. In: Sitek, P., Pietranik, M., Krótkiewicz, M., Srinilta, C. (eds) Intelligent Information and Database Systems. ACIIDS 2020. Communications in Computer and Information Science, vol 1178. Springer, Singapore. https://doi.org/10.1007/978-981-15-3380-8_49

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  • DOI: https://doi.org/10.1007/978-981-15-3380-8_49

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  • Print ISBN: 978-981-15-3379-2

  • Online ISBN: 978-981-15-3380-8

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