A Review on Sarcasm Detection Based on Machine Learning

Authors

  • Vaishnavi Vhora  M.Tech Scholar, Department of Computer Science & Engineering, Guru Nanak Institute of Engineering and Technology, Nagpur, Maharashtra, India.
  • Vijaya Kamble  Assistant Professor, Department of Computer Science & Engineering, Guru Nanak Institute of Engineering and Technology, Nagpur, Maharashtra, India.

Keywords:

Sarcasm detection, Twitter, Sentiment analysis, Machine learning

Abstract

Sarcasm is a subtle form of irony, which can be widely used social networks such as twitter. It is usually used to transmit hidden information, a message sent by people. Due to a different purposes Sarcasm can be used like criticism and ridicule. But even this is difficult for a person to recognize. The sarcastic reorganization system is very helpful for the improvement of automatic sentiment analysis collected from different social networks and microblogging sites. Sentiment analysis refers to internet users of a particular community, expressed attitudes and opinions of identification and aggregation. To detecting sarcasm we propose a pattern-based approach using Twitter data. We proposes four sets of features that include a lot of specific sarcasm. We use them to classify tweets as sarcastic and non-sarcastic. We also study each of the proposed feature sets and evaluate its additional cost classifications.

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

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Published

2021-04-30

Issue

Volume 7, Issue 2, March-April-2021

Section

Research Articles

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How to Cite

[1]
Vaishnavi Vhora, Vijaya Kamble, " A Review on Sarcasm Detection Based on Machine Learning" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 7, Issue 2, pp.52-57, March-April-2021.