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@article{189293,
        author = {Prof.Tarun Lambhate and Dr.Vinayak Khare},
        title = {Research paper on Fake News Identification through Artificial Intelligence},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {7},
        pages = {7244-7245},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=189293},
        abstract = {The exponential growth of digital media platforms and social networking sites has resulted in the rapid dissemination of fake news and misinformation. Fake news poses serious threats to society by influencing public opinion, spreading panic, and undermining trust in legitimate information sources. Traditional manual verification techniques are inefficient due to the massive volume and velocity of online content. This research paper presents an Artificial Intelligence-based approach for detecting fake news using machine learning and deep learning techniques. Natural Language Processing methods are employed for text preprocessing and feature extraction, followed by classification using Naïve Bayes, Support Vector Machine, and BERT models. Experimental results obtained from benchmark datasets demonstrate that deep learning models outperform traditional machine learning approaches in terms of accuracy and reliability. The proposed framework provides an effective and scalable solution for automated fake news detection and can be deployed in real-time digital environments.},
        keywords = {Fake News Detection, Artificial Intelligence, Machine Learning, Deep Learning, Natural Language Processing, IJIRT},
        month = {December},
        }