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Various Approaches for Fake News Detection

Chaitra.B Ramya P Sai Swaroopa A Shubha B K Sindhu S N

Subject area: Science,Engineering and Technology  ·  Area of research: Machine Learning

Abstract

Traditional media has been changed via way of means of online network and has end up as main platform for spreading fake news. Access to the Internet has led to create faster and easier ways of communication through social media instead of traditional news sources. Fake news can be spread easily from unverified sources which may mislead the readers. Detecting fake news was accomplished manually in the past which was tedious, but now there are many automated methods which uses machine learning techniques and other related fields which reduces human effort. This paper provides comparison and evaluation of various machine learning techniques in different social media platforms. These techniques include classification algorithms like Naive Bayes and other deep learning algorithms like CNN, RNN, LSTM.

Keywords

deep learning, fake news, online network, machine learning.

References

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How to cite this paper

Chaitra.B, Ramya P, Sai Swaroopa A, Shubha B K, Sindhu S N "Various Approaches for Fake News Detection" Iconic Research And Engineering Journals Volume 5 Issue 1 2021 Page 329-334
Chaitra.B, Ramya P, Sai Swaroopa A, Shubha B K, Sindhu S N "Various Approaches for Fake News Detection" Iconic Research And Engineering Journals, vol. 5, no. 1, Jul. 2021
Chaitra.B, Ramya P, Sai Swaroopa A, Shubha B K, Sindhu S N (2021). Various Approaches for Fake News Detection. Iconic Research And Engineering Journals, 5(1).
Chaitra.B, Ramya P, Sai Swaroopa A, Shubha B K, Sindhu S N "Various Approaches for Fake News Detection" Iconic Research And Engineering Journals, vol. 5, no. 1, Jul. 2021.
@article{1702878,
      author = {Chaitra.B, Ramya P, Sai Swaroopa A, Shubha B K, Sindhu S N},
      title = {Various Approaches for Fake News Detection},
      journal = {Iconic Research And Engineering Journals},
      year = {2021},
      volume = {5},
      number = {1},
      pages = {329-334},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1702878.pdf},
      abstract = {Traditional media has been changed via way of means of online network and has end up as main platform for spreading fake news. Access to the Internet has led to create faster and easier ways of communication through social media instead of traditional news sources. Fake news can be spread easily from unverified sources which may mislead the readers. Detecting fake news was accomplished manually in the past which was tedious, but now there are many automated methods which uses machine learning techniques and other related fields which reduces human effort. This paper provides comparison and evaluation of various machine learning techniques in different social media platforms. These techniques include classification algorithms like Naive Bayes and other deep learning algorithms like CNN, RNN, LSTM.},
      keywords = {deep learning, fake news, online network, machine learning.},
      month = {July},
  }