The impact of fake news in the present-day world is very high. It has the potential to alter anything irrespective of the profile. Not all fake news is dangerous but some may even ruin the lives of many. There are a lot of existing Fake News Detecting models but most of them mainly struggle to achieve and maintain the accuracy of the model as well as consistent updating of the datasets. Some models face difficulty in multi-language detection while other models struggle in automatic language detection. The proposed model serves as a solution for all the above-mentioned problems and it also includes web scrapping. The cross-dataset experimentation is performed using machine learning techniques for impactful results which primarily focus on Indian news. This model outperforms existing standards with an astonishing 99% accuracy using the logistic regression algorithm.
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Mahesh et al. (2024) studied this question.
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