7-days of FREE Audio papers, translation & more with Prime
7-days of FREE Prime access
7-days of FREE Audio papers, translation & more with Prime
7-days of FREE Prime access
https://doi.org/10.1109/icdcece53908.2022.9793155
Copy DOIPublication Date: Apr 23, 2022 |
Citations: 2 |
Fake news of social media is growing rapidly. The exponential growth and clean get right of entry to of the facts available on social media networks has made it elaborate to distinguish among fake and real news. Detecting fake news is very important. To identify the fake news detection techniques are proposed in Machine Learning and Deep Learning. In this Recurrent Neural Network method is used to determine whether or not the information is actual or fake information. Fake news will mislead and create wrong perceptions among the people. This paper explores different textual properties which are used to distinguish between real and fake news. In this, datasets of fake and true news are used to train the model using proposed algorithm. The accuracy of the model will show the efficiency of the system
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.