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Correction | Open Access

Correction: A Transformer-Based Deep Learning Framework with Semantic Encoding and Syntax-Aware LSTM for Fake Electronic News Detection

Hamza Murad Khan1, Shakila Basheer2, Mohammad Tabrez Quasim3, Raja`a Al-Naimi4, Vijaykumar Varadarajan5, Anwar Khan1( )
Department of Electronics, University of Peshawar, Peshawar, 25120, Pakistan
Department of Information Systems, College of Computer and Information Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia
Department of Computer Science and Artificial Intelligence, College of Computing and Information Technology, University of Bisha, P.O. Box 551, Bisha, 61922, Saudi Arabia
Department of Mathematics, University of Petra, Amman, 1199, Jordon
School of Computer Science, University of Technology, Sydney, 2007, Australia
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The online version of the original article can be found at:
https://doi.org/10.32604/cmc.2025.069327

Keywords

Fake news detectiontokenizationSMOTEtest-to-text transfer transformer (T5)long short-term memory (LSTM)self-attention mechanism (SA)T5-SA-LSTMWELFake datasetFakeNewsPrediction dataset

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Computers, Materials & Continua
Volume 88 Issue 3,
July 2026
Article number: 108
DOI: 10.32604/cmc.2026.087222

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Khan HM, Basheer S, Tabrez Quasim M, et al. Correction: A Transformer-Based Deep Learning Framework with Semantic Encoding and Syntax-Aware LSTM for Fake Electronic News Detection. Computers, Materials & Continua, 2026, 88(3): 108. https://doi.org/10.32604/cmc.2026.087222

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Published: 23 July 2026
© The Author 2026.

This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.