Sentiment analysis enhancement with target variable in Kumar's Algorithm

Content Provider	Scilit
Author	Arman, A. A. Kawi, A. B. Hurriyati, R.
Copyright Year	2016
Description	Journal: Iop Conference Series: Materials Science and Engineering Sentiment analysis (also known as opinion mining) refers to the use of text analysis and computational linguistics to identify and extract subjective information in source materials. Sentiment analysis is widely applied to reviews discussion that is being talked in social media for many purposes, ranging from marketing, customer service, or public opinion of public policy. One of the popular algorithm for Sentiment Analysis implementation is Kumar algorithm that developed by Kumar and Sebastian. Kumar algorithm can identify the sentiment score of the statement, sentence or tweet, but cannot determine the relationship of the object or target related to the sentiment being analysed. This research proposed solution for that challenge by adding additional component that represent object or target to the existing algorithm (Kumar algorithm). The result of this research is a modified algorithm that can give sentiment score based on a given object or target.
Related Links	http://iopscience.iop.org/article/10.1088/1757-899X/128/1/012019/pdf
ISSN	17578981
e-ISSN	1757899X
DOI	10.1088/1757-899x/128/1/012019
Journal	Iop Conference Series: Materials Science and Engineering
Issue Number	1
Volume Number	128
Language	English
Publisher	IOP Publishing
Publisher Date	2016-04-01
Access Restriction	Open
Subject Keyword	Journal: Iop Conference Series: Materials Science and Engineering Sentiment Analysis Kumar Algorithm Object Or Target Algorithm Sentiment
Content Type	Text
Resource Type	Article