DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Electronics and Computer Science-IJAECS |
 Journal Home Volume Issue |
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Issue |
Volume-9,Issue-6 ( Jun, 2022 ) | |||||||||
Paper Title |
A Systematic Study of Fake News Detection Algorithms using Deep Learning Techniques | |||||||||
Author Name |
Nipun Bansal, Mitranshu Raj | |||||||||
Affilition |
1Assistant Professor, Department of Computer Science and Engineering Delhi Technological University, Delhi, India 2Department of Computer Science and Engineering, Delhi Technological University, Delhi, India | |||||||||
Pages |
13-17 | |||||||||
Abstract |
Abstract - In today’s ever-growing internet, information and news spreads rapidly like wildfire. A fraction of this news is fake or misleading, mostly for political purposes. These fake news need to be monitored. Since the amount of information generated everyday is gigantic, it is only viable to automate the fake news detection procedure. In this paper, we have thoroughly gone through various deep learning and neural network techniques that can be applicable for fake news detection. We have compared these algorithms based on their architecture and mode of operation in terms of the problem statement. Keywords - Fake News Detection System, RNN, LSTM, Bi- directional LSTM | |||||||||
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