Evaluation of Machine Learning Approaches for Classification of Fake News

Authors

  • Reeya Baria  Research Student, Department of Computer Engineering, Sigma Institute of Engineering, Vadodara, Gujarat, India
  • Sheshang Degadwala  Associate Professor, Department of Computer Engineering, Sigma Institute of Engineering, Vadodara, Gujarat, India
  • Rocky Upadhyay  Assistant Professor, Department of Computer Engineering, Sigma Institute of Engineering, Vadodara, Gujarat, India
  • Dhairya Vyas  Managing Director, Shree Drashti Infotech LLP, Vadodara, Gujarat, India

DOI:

https://doi.org//10.32628/CSEIT228310

Keywords:

Indian Language, social media, Sematic Feature, Entity Finding and Machine Learning

Abstract

Due to the obvious easy accessibility and exponential increase of information accessible on social media channels, differentiating between bogus and authentic information has become challenging. As a consequence, some scholars are concentrating on identifying bogus news. The bulk of saliency detection tools focus on the device's linguistic properties. However, they have problems recognizing particularly ambiguous false news, that could only be detected after establishing the content and most current linked information. To solve this problem, this research will provide a new Indian false news detection method based on a factual data base that's also generated and refreshed by human morality after accumulating evident facts. Our system takes a hypothesis and scans the Fact central database for conceptually similar stories in order to assess whether the given claim is false or not before contrasting it to the similar stories. To bypass these limits, the review will describe a unique matching strategy that takes use of all the article streamlining and entity discovery sets. In this survey we learned different machine learning algorithms and its functionality with its benefits and downsides.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2022-05-30

Issue

Volume 8, Issue 3, May-June-2022

Section

Research Articles

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How to Cite

[1]
Reeya Baria, Sheshang Degadwala, Rocky Upadhyay, Dhairya Vyas, " Evaluation of Machine Learning Approaches for Classification of Fake News, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 3, pp.30-44, May-June-2022. Available at doi : https://doi.org/10.32628/CSEIT228310