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Fake News Detection Using Machine Learning and Deep Learning Classifiers

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ICT for Intelligent Systems ( ICTIS 2023)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 361))

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Abstract

To read the news, most smartphone users prefer social networking sites over the internet. The news is posted on news websites, and the source of the verification is cited. The problem is determining how to verify the news and publications shared via online communities like Tweet, Pages on FB, WhatsApp Groups, as well as other microblogs as well as social channels. It is damaging to society to hold on to rumors masquerading as news. The request for an end to speculations, particularly in develo** countries such as India, with a focus on authenticated, accurate news reports. Fake news has spread to a larger audience than ever before in this digital era, owing primarily to the rise of social media and direct messaging platforms. False information detection requires significant research, but it also presents some challenges. Some difficulties may arise as a result of a limited number of resources, such as a dataset.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, M. Kumarasamy College of Engineering, Thalavapalayam, Karur, Tamil Nadu, India

    C. Nandhakumar, C. Kowsika, R. Reshema & L. Sandhiya

Authors
  1. C. Nandhakumar
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  2. C. Kowsika
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  3. R. Reshema
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  4. L. Sandhiya
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Corresponding author

Correspondence to C. Nandhakumar .

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Editors and Affiliations

  1. Hertfordshire Business School, University of Hertfordshire, Hatfield, Hertfordshire, UK

    Jyoti Choudrie

  2. Department of Artificial Intelligence and Data Science, Vishwakarma Institute of Information Technology, Pune, Maharashtra, India

    Parikshit N. Mahalle

  3. University Putra Malaysia, Serdang, Selangor, Malaysia

    Thinagaran Perumal

  4. Global Knowledge Research Foundation, Ahmedabad, Gujarat, India

    Amit Joshi

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Nandhakumar, C., Kowsika, C., Reshema, R., Sandhiya, L. (2023). Fake News Detection Using Machine Learning and Deep Learning Classifiers. In: Choudrie, J., Mahalle, P.N., Perumal, T., Joshi, A. (eds) ICT for Intelligent Systems. ICTIS 2023. Smart Innovation, Systems and Technologies, vol 361. Springer, Singapore. https://doi.org/10.1007/978-981-99-3982-4_14

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