Fake News Detection on Social Media Platform

Authors:

Sankar.M

Department of Computer Appliations-(PG)

Hindustan College of Arts and Science-Coimbatore,India

24mca076@hicas.ac.in

Dr.Sri Devi.R

Department of Computer Appliations-(PG)

Hindustan College of Arts and Science-Coimbatore,India

ORCID:0000-0002-3946-4967

Abstract:

The rapid growth of digital media and online news platforms has significantly increased the spread of fake news, which can negatively influence public opinion and social stability. Identifying misleading or false information manually is time-consuming and often unreliable. Existing technologies for fake news detection primarily use Machine Learning and Natural Language Processing techniques such as TF-IDF, Logistic Regression, SVM, and deep learning models to automatically classify news content as real or fake.The presented work web developed with an interactive and user-friendly web application is developed using Stream-lit, allowing users to verify news content through URL input, keyword search, or manual text entry. News content is extracted using Newspaper3k and live news is fetched using the G News API.The system provides fast and accurate predictions with a clean, dark-themed interface and supports both local execution and cloud deployment. This paper demonstrates how Machine Learning can be effectively applied to combat the spread of fake news in real-world applications. The Limitation-of the system relies mainly on textual analysis and may not accurately detect fake news involving multimedia content or complex contextual meanings.Future Work of the system can be enhanced by integrating deep learning models, multilingual support, multimedia analysis, and explainable AI techniques to improve accuracy and scalability.The Fake News Detection system was successfully developed and deployed using Machine Learning and Stream-lit. The trained Logistic Regression model combined with TF-IDF vectorization demonstrated effective performance in classifying news articles as Real or Fake.

Keywords: Machine Learning, Fake News Detection, Natural Language Processing, TF-IDF, Logistic Regression, Streamlit, Text Classification,GNews API.