Fake News Detection using Support Vector Machine

Alpna Patel, Arvind Kumar Tiwari, S. S. Ahmad

2021

Abstract

Social media is a rich source of information now days. If we look into the dark side of social media, we observed that fake news is one of the serious issues of society. Fake news is being used to spread false information over social media platforms. Fake news detection is the substantial area of research in the field of Natural Language Processing. Thispaper gives the comparative study of well-known machine learning approaches like Naïve Bayes, SVM, Decision tree classifier, Random Forest, Multinomial NB and Logistic Regression. The experimental result shows that SVM classifier outperforms the other approaches and achieved accuracy of 94.93%.

Paper Citation

in Harvard Style

Patel A., Tiwari A. and Ahmad S. (2021). Fake News Detection using Support Vector Machine. In Proceedings of the 3rd International Conference on Advanced Computing and Software Engineering - Volume 1: ICACSE, ISBN 978-989-758-544-9, pages 34-38. DOI: 10.5220/0010562000003161

in Bibtex Style

@conference{icacse21,
author={Alpna Patel and Arvind Kumar Tiwari and S. S. Ahmad},
title={Fake News Detection using Support Vector Machine},
booktitle={Proceedings of the 3rd International Conference on Advanced Computing and Software Engineering - Volume 1: ICACSE,},
year={2021},
pages={34-38},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010562000003161},
isbn={978-989-758-544-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Advanced Computing and Software Engineering - Volume 1: ICACSE,
TI - Fake News Detection using Support Vector Machine
SN - 978-989-758-544-9
AU - Patel A.
AU - Tiwari A.
AU - Ahmad S.
PY - 2021
SP - 34
EP - 38
DO - 10.5220/0010562000003161