Paper Key : IRJ************571
Author: Bairagoni Bhargavi,Chitrada Sandeep,Devarasetty Sai Ram
Date Published: 02 Mar 2024
Abstract
The easy access and exponential growth of the information available on social media networks has made it intricate to distinguish between false and true information. Apart from that the extensive spread of fake news can have a serious impact on society. Majorly fake news can break the standard balance of the way society works. It might get people into believing into false content that might cause serious harm to ones property. Fake news is usually spread by certain group of people in the society who have certain politicalconnections or attempt to make free money out of oneshard earning. Most important thing is that fake news changes the way people think and they intend to doubt on each and every other news even if it is real.The application introduces an efficient method for detecting fake news in real time. The application is designed for simplicity, allowing users to upload text directly and receive instant feedback on the likelihood of manipulation of the news. The strength of this approach lies in its real-time capabilities and ease of use. As it relies on natural language process, The system continually improves its accuracy with exposure to new instance of fake news. This paper demonstrates a model and the methodology for fake news detection. With the help of Machine learning and natural language processing, it is tried to aggregate the news and later determine whether the news is real or fake using django. The results of the proposed model is compared with existing models. The proposed model is working well and defining the correctness of results upto 93.6% of accuracy.