e-ISSN:0976-5166
p-ISSN:2231-3850


INDIAN JOURNAL OF COMPUTER SCIENCE AND ENGINEERING

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ABSTRACT

Title : A SURVEY ON SARCASM DETECTION APPROACHES
Authors : JIHAD ABOOBAKER, Dr E. ILAVARASAN
Keywords : Sentiment analysis; sarcasm detection; machine learning; deep learning.
Issue Date : Nov-Dec 2020
Abstract :
Natural Language Processing (NLP) is always one of the interesting topics among researchers. To understand the perfect meaning of what depicted in the conversation is always a helping factor to solve different tasks and enhance the accuracy of different applications. Sentiment analysis uses the NLP techniques and learning models like machine learning and deep learning algorithms to understand sentiments expressed in the given data. Sentiment analysis is an approach to find the contextual meaning expressed in the textual data. Sarcasm detection comes as part of sentiment analysis because sarcasm is a kind of sentiment where individuals convey their feelings about a particular topic indirectly. People means the entire opposite of the surface content of the sentence. This unique characteristic of the sarcastic sentence makes it difficult to plot sarcasm. This paper will discuss the works done in the area of sarcasm detection, different techniques and challenges in sarcasm detection.
Page(s) : 751-771
ISSN : 0976-5166
Source : Vol. 11, No.6
PDF : Download
DOI : 10.21817/indjcse/2020/v11i6/201106048