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@article{163170,
        author = {Anushka Bipin Khandagale and B. N. Babar and Pratham More and Yash Malvade and Shubham Kokane},
        title = {The Fake News Filter: Separating Fact from Fiction},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {11},
        pages = {957-961},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=163170},
        abstract = {Most of the smart phone users prefer to read the news via social media over internet. The news websites are publishing the news and provide the source of authentication. The question is how to authenticate the news and articles which are circulated among social media like WhatsApp groups, Facebook Pages, Twitter and other micro blogs & social networking sites. It is harmful for the society to believe on the rumors and pretend to be a news. The need of an hour is to stop the rumors especially in the developing countries like India, and focus on the correct, authenticated news articles. 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 Support Vector Machine. 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.},
        keywords = {Artificial Intelligence Prediction, Recommendation, Support Vector Machine Machine Learning.},
        month = {},
        }