Fake News Detection using Machine Learning: A Comprehensive Analysis

Authors

  • Nidhi Singh Kushwaha Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University Uttar Pradesh, Lucknow Campus, India
  • Dr. Pawan Singh Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University Uttar Pradesh, Lucknow Campus, India https://orcid.org/0000-0002-1342-9493

DOI:

https://doi.org/10.54060/JMSS/002.01.001

Keywords:

Fake News, Machine Learning, News Detection, Algorithms

Abstract

Fake news today is an important fact or the life of social media and in the political world. False news discovery is an important study that should be done for its discovery but there are some challenges as well. Some challenges may be due to the small number of similar resources available collection of data and publications. We suggest in this paper, the discovery of false information using machine learning techniques. We compare three different stages of machine learning strategies. Not only that, but we will be working with three different models namely Logistic Regression, Decision Tree Classifier, and Random Forest Classification. According to the discovery of our project, we have gained your various accuracy each way in sequence. Our project can greatly benefit from finding out if the given information is true or fake.

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Published

2022-02-25

How to Cite

[1]
N. Singh Kushwaha and P. Singh, “Fake News Detection using Machine Learning: A Comprehensive Analysis”, J. Manage. Serv. Sci., vol. 2, no. 1, pp. 1–15, Feb. 2022.

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