A Collection of Contemporary Research Articles in Electronics, Communication & Computation- Book ISBN- 978-81-948050-7-6

Authors: Jayendra Kumar, Anumeha, Arvind R.Yadav, M. Ramesh Naik

Abstract: Fake News is false information about any existing original news content or intentionally fabricated for any specific purpose. Since the spread of news is more being used in an online manner, it’s challenging to detect fake news automatically before it leads to any serious damage. Many researches have been done to differentiate between fake or real news content, using different dataset and algorithms. We introduce a comparative experiment on various classification algorithms and develop an efficient machine learning model to detect whether the news is fake or real. The experiment is done on two different formats of the dataset, which are mostly affected by fake news content, i.e., blog based (Face- book post) and linguistic-based news content. Thus, developing an efficient model with high accuracy and detecting the veracity of news in different format of news. We achieve an accuracy of 97.5% with the linguistic dataset and 75.5% with the Facebook post-based dataset.

Keywords: Machine learning, Fake news detection, Classifier algorithm, Facebook post, Linguistic news.