Open AccessSarcasm Detection Using Different Machine Learning Algorithms
Author(s) -
Harshal Surve,
Aditya Mestry
Publication year - 2021
Publication title -
international journal of advanced research in science, communication and technology
Language(s) - English
Resource type - Journals
ISSN - 2581-9429
DOI - 10.48175/ijarsct-1594
Subject(s) - sarcasm , artificial intelligence , support vector machine , computer science , machine learning , sentence , naive bayes classifier , meaning (existential) , algorithm , natural language processing , psychology , irony , linguistics , philosophy , psychotherapist
Sarcasm is the use of words usually used to indirectly either mock or annoy someone, or for humorous purposes. One of the difficult modes of communication for machines to identify is sarcasm. People often use sarcasm in their daily communication to indirectly annoy people which makes it very important to identify the sentence meaning. There are various machine learning algorithms for sarcasm detection such as Naïve Bayes (NB), Support Vector Machine (SVM), Logistics Regression (LR), Decision Trees (DT).All these algorithm can be used for Sarcasm Detection. The main goal of this paper is to provide various machine learning algorithms for sarcasm detection.