A Novel Integrated Framework for Sarcasm Detection in Social Platform

Abstract

Sarcasm is a form of speech which transforms the verbatim meaning of a sentence into its antonym. Sarcasm identification in social media is a crucial facet of the sentiment analysis process, since it deals with texts whose polarity is completely opposite from its utterance. Our paper provides an exhaustive review of the existing methodologies dedicated to the task of detecting sarcasm in texts posted on an online forum. A comparative analysis of the existing techniques, mentioning the datasets and the performance measure, is also provided. This paper also introduces a novel integrated framework for identifying sarcastic clues in tweets, and recognizing sarcastic users.