ItemConference Paper

Detecting and Countering Misinformation Through NLP-Based Approach for Fake News Detection

Title
Detecting and Countering Misinformation Through NLP-Based Approach for Fake News Detection
Creator
Jayadharshini, P.; Vasuki, C.; Krishnasamy, Lalitha; Rakshitaa, J.; Abarna, N.; Kannan, N.
Description
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.
Source
Lecture Notes in Networks and Systems;Volume;1314 LNNS;pp.101-113
Date
01-01-2025
Publisher
Springer Science and Business Media Deutschland GmbH
Subject
5 g; Fake news detection; Gradient boosting classifier; N-grams; Tokenization
Coverage
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
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISSN: 23673370; ISBN: 978-981963796-6;
Format
online
Language
English
Type
Conference paper

Citation

Jayadharshini, P.; Vasuki, C.; Krishnasamy, Lalitha; Rakshitaa, J.; Abarna, N.; Kannan, N., “Detecting and Countering Misinformation Through NLP-Based Approach for Fake News Detection,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 19, 2026, https://archives.christuniversity.in/items/show/25517.

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