Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Jayadharshini, P.; Vasuki, C.; Krishnasamy, Lalitha; Rakshitaa, J.; Abarna, N.; Kannan, N. Title A name given to the resource Detecting and Countering Misinformation Through NLP-Based Approach for Fake News Detection Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems;Volume;1314 LNNS;pp.101-113 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-96-3797-3_9" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-96-3797-3_9</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105031511014?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105031511014?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Jayadharshini P., Department of Artificial Intelligence, Kongu Engineering College, Tamil Nadu, Perundurai, India; Vasuki C., Department of Information Technology, Nandha Engineering College, Tamil Nadu, Perundurai, India; Krishnasamy L., Department of CSE, School of Engineering and Technology, CHRIST University, Kengeri, Bangalore, India; Rakshitaa J., Department of Artificial Intelligence, Kongu Engineering College, Tamil Nadu, Perundurai, India; Abarna N., Department of Artificial Intelligence, Kongu Engineering College, Tamil Nadu, Perundurai, India; Kannan N., Department of Artificial Intelligence, Kongu Engineering College, Tamil Nadu, Perundurai, India Description An account of the resource The rapid expansion of digital media and the seamless transmission of information have raised serious concerns about the widespread dissemination of misinformation and fake news. Combatting this issue requires robust and effective techniques that can accurately detect and classify fake news. Natural language processing (NLP) approaches have emerged as powerful tools in this endeavor, leveraging advanced text classification algorithms to identify and counteract misinformation. This study includes NLP approaches for countering misinformation through text classification, with a specific focus on fake news detection. Leveraging natural language processing techniques, the project implements a text classification pipeline for identifying and distinguishing between genuine and fake news. The pipeline encompasses essential NLP steps such as tokenization and stop word removal. Traditional machine learning algorithms, such as the gradient boosting classifier, CatBoost classifier, random forest classifier, AdaBoost classifier, logistic regression, and SVM linear kernel are trained using the transformed data to classify news articles. This study explores feature engineering techniques and model evaluation to enhance the classification performance. Experimental results indicate the effectiveness of The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. Subject The topic of the resource 5 g; Fake news detection; Gradient boosting classifier; N-grams; Tokenization Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-981963796-6; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online