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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/123456789/8230
Title: Thin Servers for the Internet of Things
Authors: Sharma, Yashvardhan
Keywords: Computer Science
Feature extraction
Pattern matching
Sentiment Analysis
Twitter
Companies
Issue Date: Mar-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/keywords#keywords
http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8230
Appears in Collections:Department of Computer Science and Information Systems

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