Tackling Fake News in Bengali: Unraveling the Impact of Summarization vs. Augmentation on Pre-trained Language Models

TL;DR

This paper explores the use of summarization and augmentation techniques with pre-trained language models to improve fake news detection in Bengali, a low-resource language, demonstrating high accuracy through extensive experiments.

Contribution

It introduces a novel methodology combining summarization and augmentation for Bengali fake news detection using multiple pre-trained models, addressing low-resource challenges.

Findings

BanglaBERT with augmentation achieved 96% accuracy

Summarized augmented news improved detection accuracy

mBERT achieved 86% accuracy on generalization dataset

Abstract

With the rise of social media and online news sources, fake news has become a significant issue globally. However, the detection of fake news in low resource languages like Bengali has received limited attention in research. In this paper, we propose a methodology consisting of four distinct approaches to classify fake news articles in Bengali using summarization and augmentation techniques with five pre-trained language models. Our approach includes translating English news articles and using augmentation techniques to curb the deficit of fake news articles. Our research also focused on summarizing the news to tackle the token length limitation of BERT based models. Through extensive experimentation and rigorous evaluation, we show the effectiveness of summarization and augmentation in the case of Bengali fake news detection. We evaluated our models using three separate test datasets. The BanglaBERT Base model, when combined with augmentation techniques, achieved an impressive accuracy of 96% on the first test dataset. On the second test dataset, the BanglaBERT model, trained with summarized augmented news articles achieved 97% accuracy. Lastly, the mBERT Base model achieved an accuracy of 86% on the third test dataset which was reserved for generalization performance evaluation. The datasets and implementations are available at https://github.com/arman-sakif/Bengali-Fake-News-Detection