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Publication Number

2301004

 

Page Numbers

1-6

Paper Details

Analysis of Fake News Detection using Support Vector Machine

Authors

Satish Chadokar, Anchal Farkade, Kajal Deshmukh, Aanchal Khandelwal, Nisha Barasker

Abstract

Fake News is an unwanted buzz projected to influence the thoughts of masses. Over the last decade, especially in India netizens have augmented. Along with this popularity of social media is soaring high. It has become convenient to put anything on websites using current technologies. The Internet is perfect for procreating malicious and false facts as news. They hold power to change opinions and the way people should think about subjects. In this document we study and propose an idea of system for fake news detection that uses machine learning methodologies to reduce confusion caused due to fake news. We trace the paths of previously proposed models to deeply study and understand essence of the objective to build the model.

Keywords

Machine Learning, Classifiers, Naïve Bayes, Support Vector Machine (SVM), Natural Language Processing

 

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Citation

Analysis of Fake News Detection using Support Vector Machine. Satish Chadokar, Anchal Farkade, Kajal Deshmukh, Aanchal Khandelwal, Nisha Barasker. 2023. IJIRCT, Volume 9, Issue 1. Pages 1-6. https://www.ijirct.org/viewPaper.php?paperId=2301004

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