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Online Fake News Detection Using Machine Learning Techniques: A Systematic Mapping Study

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Combating Fake News with Computational Intelligence Techniques

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1001))

Abstract

This last decade, the amount of data exchanged on the Internet and more specifically on social media networks is growing exponentially. Fake News phenomenon has become a major problem threatening the credibility of these social networks. Machine Learning (ML) techniques represent a promising solution to deal with this issue. For that, several solutions and algorithms using Machine Learning have been proposed in literature in the recent time for detecting fake news generated by different digital media platforms. This chapter aims to conduct a systematic mapping study to analyze and synthesize studies concerning the utilization of machine learning techniques for detecting fake news. Therefore, a total number of 76 relevant papers published on this subject between 1 January 2010 and 30 June 2021 were carefully selected. The selected articles were classified and analyzed according to eight criteria: channel and year of publication, research type, study domain, study platform, study context, study category, feature, and machine learning techniques used to handle categorical data. The results showed that most of the selected papers use both features text/content and linguistic to design machine learning models. Furthermore, SVM technique, and Deep Neural Network (DNN) technique were the most binary classification algorithms used to combat fake news.

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Authors and Affiliations

  1. University Hassan II, Casablanca, Morocco

    Mohamed Lahby & Youness Abakarim

  2. Faculty of sciences and Technology of Mohammedia, University Hassan II, Casablanca, Morocco

    Said Aqil

  3. Department of Computer Science, College of Computer Science and Engineering, Taibah University, Madinah, Saudi Arabia

    Wael M. S. Yafooz

Authors
  1. Mohamed Lahby
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  2. Said Aqil
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  3. Wael M. S. Yafooz
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  4. Youness Abakarim
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Corresponding author

Correspondence to Mohamed Lahby .

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Editors and Affiliations

  1. Hassan II University, Casablanca, Morocco

    Mohamed Lahby

  2. United International University, Dhaka, Bangladesh

    Al-Sakib Khan Pathan

  3. Sultan Moulay Slimane University, Khouribga, Morocco

    Yassine Maleh

  4. Taibah University, Madinah, Saudi Arabia

    Wael Mohamed Shaher Yafooz

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Lahby, M., Aqil, S., Yafooz, W.M.S., Abakarim, Y. (2022). Online Fake News Detection Using Machine Learning Techniques: A Systematic Mapping Study. In: Lahby, M., Pathan, AS.K., Maleh, Y., Yafooz, W.M.S. (eds) Combating Fake News with Computational Intelligence Techniques. Studies in Computational Intelligence, vol 1001. Springer, Cham. https://doi.org/10.1007/978-3-030-90087-8_1

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