International Journal of Progressive Research in Engineering Management and Science
(Peer-Reviewed, Open Access, Fully Referred International Journal)
ISSN:2583-1062
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www.ijprems.com
editor@ijprems.com or Whatsapp at (+91-9098855509)
Paper Details
Fake News Detection Using Passive Aggressive Classifier (KEY IJP************198)
Abstract
The spread of fake news has become a significant issue in the digital age, affecting societal trust and decision-making. This paper presents a machine learning-based approach to fake news detection using the Passive-Aggressive Classifier. By leveraging natural language processing (NLP) for text preprocessing and feature extraction, the system classifies news articles as real or fake. The model demonstrates high efficiency and scalability, making it suitable for real-time applications such as social media moderation. This study highlights the effectiveness of the Passive-Aggressive Classifier for dynamic environments and provides insights into future enhancements to improve detection accuracy and applicability.
DOI LINK : 10.58257/IJPREMS38295 https://www.doi.org/10.58257/IJPREMS38295