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FAKE NEWS DETECTION USING BIDIRECTIONAL LSTM

Dr. Suma Sira Jacob 1, Jayesh Narayanan S 2, Kamalesh A R 3, Kaviya S 4
1 Associate Professor, Department of IT, Sri Krishna College of Technology, Coimbatore, India

2.3.4 Students, Department of IT, Sri Krishna College of Technology, Coimbatore, India

Abstract: Social media sites like Facebook, WhatsApp, Twitter, and Telegram have captured people's attention all around the world by disseminating false information and offering a convenient, affordable, and easy way to exchange information. In order to get personal or financial advantage from society, fake news is frequently produced in order to fool the general audience. So, several types of studies are conducted to detect false news with high accuracy in order to prevent it in order to lessen the harmful effects. We present a full evaluation of this false news detection technique during this research because of its disastrous effect, which is driven by the aforementioned problems. Also, the implementation of improvisation and the limitations of such approaches are discussed. Existing methods -    K-Means, CNN, Naives Bayes, etc. Here we have attempted to provide a more accurate classification using Bidirectional LSTM. This model marches toward the path of early detection to flag the propagators before propagation.

Keywords: Twitter, False news detection, Bidirectional LSTM.