# Detection of Bangla Fake News using MNB and SVM Classifier

arXiv: https://arxiv.org/abs/2005.14627 · HTML: https://mlsanity.com/paper/2005.14627/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 May 2020.

## Built on by (most cited first, 10 of 10)

- [Bangla Natural Language Processing: A Comprehensive Analysis of Classical, Machine Learning, and Deep Learning Based Methods](https://mlsanity.com/paper/2105.14875/) (2021)
- [From Scarcity to Capability: Empowering Fake News Detection in Low-Resource Languages with LLMs](https://mlsanity.com/paper/2501.09604/) (2025)
- [Approaches for Improving the Performance of Fake News Detection in Bangla: Imbalance Handling and Model Stacking](https://mlsanity.com/paper/2203.11486/) (2022)
- [Tackling Fake News in Bengali: Unraveling the Impact of Summarization vs. Augmentation on Pre-trained Language Models](https://mlsanity.com/paper/2307.06979/) (2023)
- [Zero-Shot Multi-Label Classification of Bangla Documents: Large Decoders Vs. Classic Encoders](https://mlsanity.com/paper/2503.02993/) (2025)
- [Breaking the Fake News Barrier: Deep Learning Approaches in Bangla Language](https://mlsanity.com/paper/2501.18766/) (2025)
- [Enhancing Ayurvedic Diagnosis using Multinomial Naive Bayes and K-modes Clustering: An Investigation into Prakriti Types and Dosha Overlapping](https://mlsanity.com/paper/2310.02920/) (2023)
- [Bangla Fake News Detection Based On Multichannel Combined CNN-LSTM](https://mlsanity.com/paper/2503.04781/) (2025)
- [Improving Bangla Linguistics: Advanced LSTM, Bi-LSTM, and Seq2Seq Models for Translating Sylheti to Modern Bangla](https://mlsanity.com/paper/2505.18709/) (2025)
- [Hybrid Feature Combinations with CNN for Bangla Fake News Classification](https://mlsanity.com/paper/2605.17481/) (2026)

## Abstract (arXiv)

Fake news has been coming into sight in significant numbers for numerous business and political reasons and has become frequent in the online world. People can get contaminated easily by these fake news for its fabricated words which have enormous effects on the offline community. Thus, interest in research in this area has risen. Significant research has been conducted on the detection of fake news from English texts and other languages but a few in Bangla Language. Our work reflects the experimental analysis on the detection of Bangla fake news from social media as this field still requires much focus. In this research work, we have used two supervised machine learning algorithms, Multinomial Naive Bayes (MNB) and Support Vector Machine (SVM) classifiers to detect Bangla fake news with CountVectorizer and Term Frequency - Inverse Document Frequency Vectorizer as feature extraction. Our proposed framework detects fake news depending on the polarity of the corresponding article. Finally, our analysis shows SVM with the linear kernel with an accuracy of 96.64% outperform MNB with an accuracy of 93.32%.