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Artificial Intelligence for Fake News

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International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 637))

Abstract

Fake news is a severe problem on social media networks, with confirmed detrimental consequences for individuals and organizations. As a result, detecting false news is a significant difficulty. In this way, the topic of new fakes and their proper detection are crucial. General knowledge states that the receiver of information must verify the sources. However, the creation of new information can be a difficult problem that requires more than a single viewpoint based on a news source. The objective of this paper is to evaluate the performance of six deep learning models for fake news detection including CNN, LSTM, Bi-LSTM, HAN, Conv-Han and Bert. We find that BERT and similar pre-trained models perform the best for fake news detection, the models are described below with their experimental setups.The models are examined against ISOT [22, 30] datasets.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Intelligent Processing Systems and Security Team, Faculty of Sciences, Mohammed V University in Rabat, Rabat, Morocco

    Imane Ennejjai, Anass Ariss, Nassim Kharmoum & Soumia Ziti

  2. National Center for Scientific and Technical Research (CNRST), Rabat, Morocco

    Nassim Kharmoum

  3. E2SN Research Team, ENSAM Rabat, Mohammed V University in Rabat, Rabat, Morocco

    Wajih Rhalem

  4. Mathematics and Applications Laboratory, Faculty of Sciences and Techniques of Tangier, Abdelmalek Essaadi University, Tetouan, Morocco

    Mostafa Ezziyyani

Authors
  1. Imane Ennejjai
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  2. Anass Ariss
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  3. Nassim Kharmoum
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  4. Wajih Rhalem
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  5. Soumia Ziti
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  6. Mostafa Ezziyyani
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Corresponding author

Correspondence to Imane Ennejjai .

Editor information

Editors and Affiliations

  1. Polish Academy of Sciences, Systems Research Institute, Warsaw, Poland

    Janusz Kacprzyk

  2. Abdelmalek Essaâdi University, Tangier, Morocco

    Mostafa Ezziyyani

  3. Department of Automatics and Applied Software, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

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Cite this paper

Ennejjai, I., Ariss, A., Kharmoum, N., Rhalem, W., Ziti, S., Ezziyyani, M. (2023). Artificial Intelligence for Fake News. In: Kacprzyk, J., Ezziyyani, M., Balas, V.E. (eds) International Conference on Advanced Intelligent Systems for Sustainable Development. AI2SD 2022. Lecture Notes in Networks and Systems, vol 637. Springer, Cham. https://doi.org/10.1007/978-3-031-26384-2_8

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