This paper is published in Volume-4, Issue-1, 2018
Area
Machine Learning
Author
Manisha Gahirwal, Sanjana Moghe, Tanvi Kulkarni, Devansh Khakhar, Jayesh Bhatia
Org/Univ
Vivekanand Education Society's Institute of Technology, Mumbai, Maharashtra, India
Pub. Date
03 March, 2018
Paper ID
V4I1-1432
Publisher
Keywords
Stance Detection, Natural Language Processing(NLP), Random Forest.

Citationsacebook

IEEE
Manisha Gahirwal, Sanjana Moghe, Tanvi Kulkarni, Devansh Khakhar, Jayesh Bhatia. Fake News Detection, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Manisha Gahirwal, Sanjana Moghe, Tanvi Kulkarni, Devansh Khakhar, Jayesh Bhatia (2018). Fake News Detection. International Journal of Advance Research, Ideas and Innovations in Technology, 4(1) www.IJARIIT.com.

MLA
Manisha Gahirwal, Sanjana Moghe, Tanvi Kulkarni, Devansh Khakhar, Jayesh Bhatia. "Fake News Detection." International Journal of Advance Research, Ideas and Innovations in Technology 4.1 (2018). www.IJARIIT.com.

Abstract

Fake news, one of the biggest new-age problems has the potential to mould opinions and influence decisions.The proliferation of fake news on social media and Internet is deceiving people to an extent which needs to be stopped.The existing systems are inefficient in giving a precise statistical rating for any given news claim. Also, the restrictions on input and category of news make it less varied. This paper proposes a system that classifies unreliable news into different categories after computing an F-score. This system aims to use various NLP and classification techniques to help achieve maximum accuracy.