UNVEILING FAKE NEWS DETECTION MODELS AND THEIR INTEGRATION INTO WEB SYSTEMS: AN EXTENSIVE INVESTIGATION
The pervasive spread of fake news poses a critical threat to information integrity, demanding swift and innovative countermeasures. Addressing this challenge, Fake News Detection System, a user-friendly web application, utilizes advanced natural language processing and machine learning techniques fo...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Kragujevac
2025-03-01
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| Series: | Proceedings on Engineering Sciences |
| Subjects: | |
| Online Access: | https://pesjournal.net/journal/v7-n1/43.pdf |
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| Summary: | The pervasive spread of fake news poses a critical threat to information integrity, demanding swift and innovative countermeasures. Addressing this challenge, Fake News Detection System, a user-friendly web application, utilizes advanced natural language processing and machine learning techniques for efficient fake news detection. Through meticulous preprocessing, including stemming and TF-IDF vectorization, the system optimizes textual data for analysis. Powered by Multinomial Naive Bayes and Passive Aggressive Classifier algorithms, Fake News Detection System ensures accurate classification. The web application's interactive interface offers immediate predictions and insightful visualizations, such as confusion matrix representations, enhancing user engagement. In navigating the intricate landscape of misinformation, Fake News Detection System stands as a concise and effective tool, demonstrating the fusion of accessible technology with advanced methodologies in the pursuit of information accuracy and authenticity. |
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| ISSN: | 2620-2832 2683-4111 |