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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/8229
Title: FAID: Feature Aftermath for Irony Discernment
Authors: Sharma, Yashvardhan
Keywords: Computer Science
Sarcasm Detection
Sentiment Analysis
Machine Learning
Natural Language Processing
Issue Date: 2019
Publisher: IEEE
Abstract: This paper deals with the impediment of identifying sarcasm in social media text which can be used to improve sentiment analysis technique. After thorough analysis, some features were identified which could help in recognition of sarcasm. In state of art, features have been extracted from the data set which embraced standalone sentences. Proposed algorithm analyzes the impact of these features and a combination of them on the review data set in which reviews had three or more sentences, so that context of sentence is also taken into consideration by the machine before classifying a review.
URI: https://ieeexplore.ieee.org/document/8776609
http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8229
Appears in Collections:Department of Computer Science and Information Systems

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