Work place: Department of Computer Science and Engineering, Maulana Azad National Institute of Technology, Bhopal, 462003, India
E-mail: pjiit2015@gmail.com
Website:
Research Interests: Computer systems and computational processes, Computational Learning Theory, Data Compression, Data Structures and Algorithms
Biography
Prajal Jain was born in Jobat, India in 1997. He is currently pursuing a bachelor’s degree in Computer Science and Engineering from Maulana Azad National Institute of Technology, Bhopal, India. His research interests include Data Structures, Algorithms and Machine Learning.
By Shubham Bauskar Vijay Badole Prajal Jain Meenu Chawla
DOI: https://doi.org/10.5815/ijieeb.2019.04.01, Pub. Date: 8 Jul. 2019
Internet acts as the best medium for proliferation and diffusion of fake news. Information quality on the internet is a very important issue, but web-scale data hinders the expert’s ability to correct much of the inaccurate content or fake content present over these platforms. Thus, a new system of safeguard is needed. Traditional Fake news detection systems are based on content-based features (i.e. analyzing the content of the news) of the news whereas most recent models focus on the social features of news (i.e. how the news is diffused in the network). This paper aims to build a novel machine learning model based on Natural Language Processing (NLP) techniques for the detection of ‘fake news’ by using both content-based features and social features of news. The proposed model has shown remarkable results and has achieved an average accuracy of 90.62% with F1 Score of 90.33% on a standard dataset.
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