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@article{187861,
        author = {Mr. saksham patil and Prof. Rasjesh Nasare and Mr. Roshan Manekar and Mrs. Riya Shiwankar and Mr. Mayank Deshmukh and Mr. Om Raipurkar and Mr. Roshan Dangre},
        title = {Fake News Detection Using Explainable Artificial Intellingence(XAI)},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {6},
        pages = {7458-7462},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=187861},
        abstract = {The dissemination of artificial news on online platforms has become a key issue in the current information-based society. While deep learning and machine learning algorithms have proven useful for identifying artificial news, they are frequently not interpretable. This paper presents a Fake News Detection framework utilizing Explainable Artificial Intelligence (XAI) methods like SHAP and LIME. Through the integration of Natural Language Processing (NLP) and explainable AI, the system guarantees correct classification, as well as clear reasoning for every prediction. The technique increases the trust, accountability, and useability of AI systems for end-users, policymakers, and journalists.},
        keywords = {Fake News Detection, Explainable AI, Natural Language Processing, LIME, SHAP, Trustworthy AI},
        month = {March},
        }