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@article{178302,
        author = {Nidhi H and Kavyashree N and Ishha Jaiswal and Harsh Vardhan Singh and Aparna},
        title = {Fake News Detection Using Natural Language Processing},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {4200-4203},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178302},
        abstract = {The rapid dissemination of fake news across digital platforms has become a significant societal concern, influencing public opinion, elections, and social stability. Leveraging Natural Language Processing (NLP), this research presents an automated approach to detecting fake news through linguistic analysis and deep learning techniques. Traditional machine learning methods such as SVMs and Naive Bayes classifiers have been compared with advanced models like BERT. Despite technological advancements, challenges such as evolving misinformation tactics and dataset limitations persist. This paper explores existing methodologies, highlights critical challenges, and proposes an efficient model utilizing NLP in identifying misinformation and deep learning techniques for enhanced detection of fake news. The research highlights key methodologies, challenges, and future directions, emphasizing the importance of interdisciplinary collaboration and ethical considerations in combating fake news.},
        keywords = {Fake News Detection, Natural Language Processing, Deep Learning, BERT, Machine Learning},
        month = {May},
        }