Sarcasm Detection: A Contemporary Research Affirmation of Recent Literature

Author:

Sayeedunnisa S.ORCID,Hegde Nagaratna Parameshwar,Ur Rahman Khan Khaleel

Abstract

Sarcasm identification is a confined research area in NLP, a specific case of opinion mining where the focal point in the process is identification of sarcasm, instead of sentiment extraction. Sarcasm is a specific type of opinion which is expressed as a negative feeling in form of anger, frustration, or derision veiled by the intense positive words in the text. Detection of sarcasm, which is an elusive problem for machines, has gained wide popularity in the research community in recent years. Accurate identification and analysis of sarcasm improves the performance of sentiment identification models. This manuscript details various sarcasm detection approaches, models and features used, issues, challenges, and further research scope. The various machine learning and deep learning models used to identify sarcasm are detailed in this script.

Publisher

The Electrochemical Society

Subject

General Medicine

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Effective Automated Transformer Model based Sarcasm Detection Using Multilingual Data;Multimedia Tools and Applications;2023-10-27

2. Meta-transfer Learning for Contextual Emotion Detection in Face Affirmation;Communications in Computer and Information Science;2023

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