Online Fake News Detection using Machine Learning and Natural Language Processing Algorithms

Title

Online Fake News Detection using Machine Learning and Natural Language Processing Algorithms

Creator

Vincent, Stephin Tom; George, Jossy; Kumar, Pawan

Description

Fake news in the digital platforms plays a vital threat to many of the influencing factors of the society. The research focuses on the challenges of online fake news detection from the performance achieved by the machine learning classifiers using the natural processing techniques. Logistic Regression and Random Forest are taken to test the dataset containing labelled fake and real news for the study. The models are evaluated using the key metrices as accuracy, precision, recall, F1-score, confusion matrix and from the ROC AUC score. The research demonstrates which model is more reliable and more consistent for finding the fake and real news. For semantic text analysis BERT embeddings are used in the research as it will help analyze the article with more accuracy and precision. The metrics evaluation and the ROC curve of the both models helps in knowing even the slight deviations projected in the metrics. The differences in the valuations and the metrics values showed the capabilities of both the models in detecting the online news as fake or real. The comparisons made from the two models helps in evaluating the models and to understand the limitations of it as the analyze and detection of the text is more complicated. The research aims to deliver a strong foundation for real-time fake news detection in this new era. 2025 IEEE.

Source

2025 World Skills Conference on Universal Data Analytics and Sciences, WorldSUAS 2025;

Date

01-01-2025

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

BERT; Fake News Detection; Logistic Regression; Machine Learning; Natural Language Processing; Precision-Recall; Random Forest; ROC AUC; Text Classification

Coverage

Vincent S.T., CHRIST (Deemed to Be University), India; George J., CHRIST (Deemed to Be University), India; Kumar P., CHRIST (Deemed to Be University), India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISBN: 979-833153925-2;

Format

online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/WorldSUAS66815.2025.11199266

https://www.scopus.com/pages/publications/105022238751?origin=resultslist