International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 8, Issue 5 (September-October 2026) Submit your research before last 3 days of October to publish your research paper in the issue of September-October.
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Volume 8 Issue 5
September-October 2026

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Benchmarking Naive Bayes, SVM, KNN, and Decision Tree for Fake News Classification: A Comparative Study

Author(s) Ms. Priya Jain, Dr. Hukum Chand Saini, Dr. Rishi Kumar Sharma
Country India
Abstract Fake news dissemination through digital and social media platforms has become a significant challenge, influencing public opinion, spreading misinformation, and creating societal concerns. The development of an efficient fake news detection system is therefore essential to ensure the reliability and authenticity of online information. This study proposes a Decision Tree Machine Learning Technique for efficient fake news detection by analyzing textual features extracted from news articles, including linguistic patterns, keyword distributions, and content-based attributes. The Decision Tree algorithm is employed due to its simplicity, interpretability, and capability to handle complex classification tasks with high accuracy. The proposed model undergoes data preprocessing, feature extraction, training, and classification stages to distinguish between genuine and fake news content. Experimental evaluation demonstrates that the Decision Tree-based approach effectively improves detection accuracy while reducing computational complexity, making it suitable for real-time applications. The findings indicate that the proposed technique can serve as a reliable and scalable solution for combating misinformation and enhancing trust in digital news ecosystems.
Keywords Decision Tree, Fake News Detection, Text Classification, Online Media
Field Computer Applications
Published In Volume 8, Issue 3, May-June 2026
Published On 2026-06-25
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E-ISSN 2582-2160
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CrossRef DOI prefix of IJFMR is 10.36948/ijfmr

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