📞 +91-7667918914 | ✉️ ijarcce@gmail.com
IJARCCE Logo
International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 10, ISSUE 12, DECEMBER 2021

Fake News Detection Using Machine Learning

Prof. C. P. Lachake, Ritesh Paliwal, Akshay Patil, Tejas Chaudhari, Harshal Borse

DOI: 10.17148/DOI:

Abstract: The phenomenon of Fake news is experiencing a rapid and growing progress with the evolution of the means of communication and Social media. Fake news detection is an emerging research area which is gaining big interest. It faces however some challenges due to the limited resources such as datasets and processing and analysing techniques.In this work, we propose a system for Fake news detection that uses machine learning techniques. We used term frequency-inverse document frequency (TF-IDF) of bag of words and n-grams as feature extraction technique, and Support Vector Machine (SVM) as a classifier. We propose also a dataset of fake and true news to train the proposed system. Obtained results show the efficiency of the system.Index Terms—Fake news, Social media, Web Mining, Machine Learning, Support Vector Machine, TF-IDF.

How to Cite:

[1] Prof. C. P. Lachake, Ritesh Paliwal, Akshay Patil, Tejas Chaudhari, Harshal Borse, “Fake News Detection Using Machine Learning,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/DOI: