Fake News Detection using Machine Learning

Fake News Detection using Machine Learning

Shagun Kingaonkar, Ajinkya Bawane, Ruchi Rana, Janhavi Thool,

Nikita Kale

Computer science and engineering Rashtra Sant. Tukdoji Maharaj University, Nagpur

Abstract

In our modern society where the internet is ubiquitous, everyone relies on various online resources for news. Along with the internet in the use of social media platforms like Facebook, Dataset, WhatsApp etc. News spread rapidly among millions of users within a very short span of time. The spread of fake news has far-reaching consequences like the creation of based opinions to swaying election outcomes for the benefit of certain candidates. Moreover, spammers use appealing news headlines to generate revenue using advertisement via click- baits. In this project we aim to perform classification of various news article available online with the help of concepts of Machine Learning. We aim to provide the user with the ability to classify the news which is fake or real with the help of some algorithm used in Machine Learning. This work purposes the use of machine learning techniques to detect Fake news. In the experiments used: Support Vector Machine (SVM). The normalization method is important step for cleansing data before using the machine learning method to classify data. We are aiming Support Vector Machine result should reach the higher accuracy level. Besides of machine learning we are using HTML, Python each one of has it's individual purpose for successful creation to build fake news detection

KEYWORDS: Internet, Social Media, Fake News, Classification, Artificial Intelligence, Machine Learning, Websites,  Python,  HTML.