Machine Learning Approach for Fake News Detection

Authors

  • Vijaya Balpande Department of Computer Science and Engineering, Priyadarshini J. L. College of Engineering, Nagpur, India
  • Kasturi Baswe Department of Computer Science and Engineering, Priyadarshini J. L. College of Engineering, Nagpur, India
  • Kajol Somaiya Department of Computer Science and Engineering, Priyadarshini J. L. College of Engineering, Nagpur, India
  • Achal Dhande Department of Computer Science and Engineering, Priyadarshini J. L. College of Engineering, Nagpur, India
  • Prajwal Mire Department of Computer Science and Engineering, Priyadarshini J. L. College of Engineering, Nagpur, India

Keywords:

Machine Learning, Fake, News, Detection

Abstract

Information preciseness on Internet, especially on social media, is an increasingly important concern, but web-scale data hampers, ability to identify, evaluate and correct such data, or so called "fake news," present in these platforms. we propose a method for "fake news" detection and ways to apply it on twitter, one of the most popular online social media platforms. This method uses Naive Bayes classification model to predict whether a post on twitter will be labelled as REAL or FAKE.

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Published

06-05-2021

Issue

Section

Articles

How to Cite

[1]
V. Balpande, K. Baswe, K. Somaiya, A. Dhande, and P. Mire, “Machine Learning Approach for Fake News Detection”, IJRESM, vol. 4, no. 4, pp. 189–190, May 2021, Accessed: Jul. 13, 2024. [Online]. Available: https://journal.ijresm.com/index.php/ijresm/article/view/700