Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/57824
Title: Performance evaluation of machine learning algorithms for detecting Hindi sarcasm
Authors: Katyayan, Pragya
Joshi, Nisheeth
Issue Date: Jun-2021
Publisher: NIScPR-CSIR, India
Abstract: Sentiments, the common way people express their feelings, have been greatly influenced with the advent of Sarcasm. Being sarcastic is considered trendy and thus people use it extensively in their day-to-day language. Sentiment Analysis, also known as Opinion Mining, has encountered Sarcasm as a challenge since a long time. Sarcasm, which finds few human brains susceptible to its presence and effects, has posed to be the toughest of all problems. One of the issues with Sarcasm Detection is the numerous ways it can be expressed with. Since there has not been a perfect answer to all the Sarcasm issues, this paper attempts to analyse and evaluate the popular Machine learning techniques on mixed sarcasm types.
Page(s): 43-48
URI: http://nopr.niscair.res.in/handle/123456789/57824
ISSN: 0975-2412 (Online); 0771-7706 (Print)
Appears in Collections:BVAAP Vol.29(1) [June 2021]

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