Paper Title
Detection And Classification of Fake News Using Natural Language Processing and Deep Learning
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Registration ID: IJNRD_312404
Published ID: IJNRD2602147
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Keywords
Fake News Detection, Natural Language Processing, Deep Learning, LSTM Network, Text Classification, Misinformation Analysis
Abstract
Fake news has emerged as a major challenge in the digital information ecosystem due to the rapid growth of online news platforms and social media. The intentional dissemination of misleading or fabricated news content poses serious risks to public trust, social stability, and informed decision-making. Traditional fact-checking and manual verification mechanisms are limited by scalability, subjectivity, and delayed response, making them inadequate for handling the massive volume of digital content generated daily. To address these limitations, this research paper presents a Natural Language Processing and deep learning-based framework for automated fake news detection, developed from an empirical dissertation study. The proposed framework focuses on textual analysis of news articles and employs systematic preprocessing techniques to standardize raw data and reduce noise. Semantic feature representation is achieved using word embeddings, while a Long Short-Term Memory neural network is used to model sequential dependencies and contextual information inherent in news narratives. The model is trained using a supervised learning approach and evaluated using comprehensive classification metrics, including accuracy, precision, recall, F1-score, confusion matrix analysis, and training–validation learning curves. Experimental results demonstrate that the proposed model achieves an overall classification accuracy of 86.32 percent, with balanced precision and recall across fake and real news classes. The findings confirm stable convergence, effective generalization, and minimal overfitting, highlighting the suitability of the proposed framework as a scalable and reliable decision-support tool for combating misinformation in digital media environments.
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How To Cite (APA)
Dr P.K. Sharma, Mr. Manvendra Singh Divakar, & Ritu Lodhi (February-2026). Detection And Classification of Fake News Using Natural Language Processing and Deep Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 11(2), b373-b383. https://ijnrd.org/papers/IJNRD2602147.pdf
Issue
Volume 11 Issue 2, February-2026
Pages : b373-b383
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Paper Reg. ID: IJNRD_312404
Published Paper Id: IJNRD2602147
Research Area: Other area not in list
Author Type: Indian Author
Country: New Delhi, New Delhi, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2602147.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2602147
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