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@article{177059,
        author = {Maskan Manasa and Maddula Shantesh and Dhudukala Thapaswini and S.Vinod Reddy and Mavoori Pratussha},
        title = {AI-Powered Fact-Check & Fake News Detection Tool},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {827-832},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=177059},
        abstract = {The rise of misinformation and fake news on digital platforms has become a critical issue, influencing public opinion, policy-making, and global events.
Traditional fact-checking methods rely on manual verification, which is inefficient and slow in the fast-paced online ecosystem. This paper presents an AI-powered fact- checking tool that integrates Natural Language Processing (NLP), machine learning (ML), deep learning (DL), and knowledge graphs to automate the detection and verification of false information. The system employs real- time data retrieval, sentiment analysis, contextual verification, and credibility scoring to assess the authenticity of news articles and social media content.
Additionally, the integration of explainable AI (XAI) enhances transparency in decision-making, increasing user trust. Our model demonstrates high accuracy and recall in detecting misinformation, making it a scalable solution for mitigating the spread of fake news and improving information reliability.},
        keywords = {Fake News Detection, AI, Machine Learning, NLP, Fact-Checking, Deep Learning, Misinformation, Explainable AI, Knowledge Graphs.},
        month = {May},
        }