Combating deep-fake news in bengali: detection and prevention of manipulated social media’s content using machine learning
Md. Jane Alam1, Md. Ashikur Rahman Khan1, Ishtiaq Ahammad1, Abir Hosen1 and Joysri Rani Das1
Department of Information and Communication Engineering,Noakhali Science and Technology University,Noakhali 3814,Bangladesh1
Corresponding Author : Md. Jane Alam
Recieved : 26-September-2025; Revised : 14-January-2026; Accepted : 26-March-2026
Abstract
The rapid expansion of social media and digital news platforms has accelerated the spread of deep fake and manipulated content, posing serious risks to public trust and social stability, particularly in low-resource languages such as Bengali, which remains underexplored despite its widespread use. To address this gap, this study investigates Bengali deep fake news detection using both classical machine learning (ML) and transformer-based deep learning approaches on newly released, expert-annotated Bangla news datasets. After comprehensive data pre-processing, multiple classifiers—logistic regression (LR), decision tree (DT), random forest (RF), gradient boosting (GB), and a fine-tuned Bangla Bidirectional Encoder Representations from Transformers (BERT)—were evaluated, with careful handling of class imbalance and cross-validation (CV) for classical models. Experimental results show that performance improves consistently with larger training data, and the Bangla BERT model significantly outperforms traditional methods, achieving 94.49% accuracy, an F1-score of 89.03%, recall of 90.28%, and a receiver operating characteristic – area under the curve (ROC-AUC) of 98.36%, demonstrating superior contextual and semantic understanding of Bengali text. The findings confirm that language-specific transformer models are highly effective for combating deep fake news in Bengali and establish a strong baseline for future research and real-world deployment of misinformation detection systems in Bangla digital media.
Keywords
Bangla fake news, BERT classifier, Fake news detection, Random forest, decision tree, Artificial intelligence, Machine learning.
Cite this article
Alam M, Khan MR, Ahammad I, Hosen A, Das JR. Combating deep-fake news in bengali: detection and prevention of manipulated social media’s content using machine learning. International Journal of Advanced Computer Research. 2026;16(76):57-76. DOI : 10.19101/IJACR.2025.1570025
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