DOIONLINE 
DOIONLINE Publish In |
International Journal of Electrical, Electronics and Data Communication (IJEEDC)-IJEEDC |
 Journal Home Volume Issue |
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Issue |
Volume-12,Issue-5 ( May, 2024 ) | |||||||||
Paper Title |
Fake News Detection Using Machine Learning | |||||||||
Author Name |
Prince Yadav, Md Jahid Hossain Rana, Ramesh Kumar Yadav, Md Manwar Hossain, Ram Pujan Sah, Parul Prakram Sharma | |||||||||
Affilition |
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Pages |
30-34 | |||||||||
Abstract |
Fake news has become the order of the day due to rapid growth in number of online news sources, and social media platforms. Unrestrained distribution of false reports threatens democratic processes, public discussions as well as the possibility of a stable society. Machine learning algorithms for fake news detection are comprehensively studied in this research paper. This entails sourcing for fake and real articles then carrying out extensive pre-processing as well as feature extraction. We also explore different machine learning models such as logistic regression, support vector machines, random forests and neural networks to perform precise classification of news articles. The performance of these models is measured using evaluation metrics such as accuracy, precision, recall and F1-score. By carrying out systematic experimentation and analysis in this work, we prove that our proposed methods have high accuracy rates in terms of identifying fake news articles. Hence, there is an effort to build scalable solutions that can withstand misinformation propagation and promote digital media literacy. Keywords - Fake News, Machine Learning, Natural Language Processing, Feature Extraction, Classification | |||||||||
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