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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| Format: | Article |
| Language: | English |
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University of Kragujevac
2025-03-01
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| Series: | Proceedings on Engineering Sciences |
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| Online Access: | https://pesjournal.net/journal/v7-n1/43.pdf |
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| author | Vimal Gaur Naman Veerwal Ujjwal Chaudhary Sparsh Kadian |
| author_facet | Vimal Gaur Naman Veerwal Ujjwal Chaudhary Sparsh Kadian |
| author_sort | Vimal Gaur |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-62ff7c7f52f24aafaebe7d86cb64e870 |
| institution | DOAJ |
| issn | 2620-2832 2683-4111 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | University of Kragujevac |
| record_format | Article |
| series | Proceedings on Engineering Sciences |
| spelling | doaj-art-62ff7c7f52f24aafaebe7d86cb64e8702025-08-20T02:57:55ZengUniversity of KragujevacProceedings on Engineering Sciences2620-28322683-41112025-03-017139140410.24874/PES07.01C.006UNVEILING FAKE NEWS DETECTION MODELS AND THEIR INTEGRATION INTO WEB SYSTEMS: AN EXTENSIVE INVESTIGATIONVimal Gaur 0https://orcid.org/0000-0003-4097-1859Naman Veerwal 1https://orcid.org/0009-0001-6742-6271Ujjwal Chaudhary 2https://orcid.org/0009-0000-4361-879XSparsh Kadian 3https://orcid.org/0009-0007-8642-2333Maharaja Surajmal Institute of Technology,Delhi, India Maharaja Surajmal Institute of Technology,Delhi, India Maharaja Surajmal Institute of Technology,Delhi, India Maharaja Surajmal Institute of Technology,Delhi, India 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.https://pesjournal.net/journal/v7-n1/43.pdffake news detectiontext preprocessingnatural language processingrandom forest classifierflask framework |
| spellingShingle | Vimal Gaur Naman Veerwal Ujjwal Chaudhary Sparsh Kadian UNVEILING FAKE NEWS DETECTION MODELS AND THEIR INTEGRATION INTO WEB SYSTEMS: AN EXTENSIVE INVESTIGATION Proceedings on Engineering Sciences fake news detection text preprocessing natural language processing random forest classifier flask framework |
| title | UNVEILING FAKE NEWS DETECTION MODELS AND THEIR INTEGRATION INTO WEB SYSTEMS: AN EXTENSIVE INVESTIGATION |
| title_full | UNVEILING FAKE NEWS DETECTION MODELS AND THEIR INTEGRATION INTO WEB SYSTEMS: AN EXTENSIVE INVESTIGATION |
| title_fullStr | UNVEILING FAKE NEWS DETECTION MODELS AND THEIR INTEGRATION INTO WEB SYSTEMS: AN EXTENSIVE INVESTIGATION |
| title_full_unstemmed | UNVEILING FAKE NEWS DETECTION MODELS AND THEIR INTEGRATION INTO WEB SYSTEMS: AN EXTENSIVE INVESTIGATION |
| title_short | UNVEILING FAKE NEWS DETECTION MODELS AND THEIR INTEGRATION INTO WEB SYSTEMS: AN EXTENSIVE INVESTIGATION |
| title_sort | unveiling fake news detection models and their integration into web systems an extensive investigation |
| topic | fake news detection text preprocessing natural language processing random forest classifier flask framework |
| url | https://pesjournal.net/journal/v7-n1/43.pdf |
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