Media Manipulation Detection System Using Passive Aggressive

Authors

  • Aarti Chugh Department of Computer Science & Engineering, Amity University, Gurugram, Haryana, India Author
  • Yojna Arora Department of Computer Science & Engineering, Amity University, Gurugram, Haryana, India Author
  • Jaivardhan Singh Department of Computer Science & Engineering, Amity University, Gurugram, Haryana, India Author
  • Shobhit Department of Computer Science & Engineering, Amity University, Gurugram, Haryana, India Author
  • Ronak Department of Computer Science & Engineering, Amity University, Gurugram, Haryana, India Author

Keywords:

Fake news, machine learning, classification, Authenticity

Abstract

Due to the extreme growing use of social  media and online news media, there has been a rise in fake  news recently. It has become much easier to spread fake  news than it was before. This type of fake news, if widely  circulated, could have a significant impact. As a result, it is  necessary to take steps to reduce or distinguish between true  and false news. We design a system to verifying such type  of news and extract correct news or provide correct news  corresponding to the fake news. On a text-based dataset, we  give an overview of false news detection using various  classifiers such as Passive Aggressive Classifier, Random  forest, Logistic regression and decision tree classifier gets  better results, as seen by the work done. Also top ten  recommendations corresponding to the real news is  displayed through our proposed model.  

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References

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Published

2021-05-30

Issue

Vol. 9 No. 3 (2021): International Journal of Innovative Research in Computer Science and Technology (May) 2021

Section

Articles

How to Cite

Media Manipulation Detection System Using Passive Aggressive . (2021). International Journal of Innovative Research in Computer Science & Technology, 9(3), 48–52. Retrieved from https://acspublisher.com/journals/index.php/ijircst/article/view/11485