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Abstract

With the spread of social media, rising digitalization, and sharing information without investigation have exploded towards the mass people. This exacerbated the long-standing issue of fake news, which has become substantially more relevant in recent years because of the harm it causes to society. Manual and Automated detection system has been introduced to tackle this problem. Deep learning techniques' most recent breakthroughs make them a potential tool for identifying fake news. In this study, we proposed a Convolutional Neural Network based learning model built in association with different test feature extraction methods to recognize false news. Experimental outcomes demonstrate that the proposed study was successful in achieving a training accuracy of 0.9879 and test accuracy of 0.9867, with a recall, and F-score of 0.98 each.

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