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Hits 1 – 2 of 2
1
Sarcasm Detection And Classification To Support Sentiment Analysis: A Study In Malay Social Media
Mohd Hanafi Ahmad Hijazi
. - 2016
Abstract:
This research work conducted on sarcasm detection and classification to support sentiment analysis. The proposed work consists of two phases: (i) sarcasm detection and (ii) sentiment analysis with sarcasm detection and classification. In the first phase, the development of a mechanism for detecting sarcasm on bilingual data was explored. To achieve this, a feature extraction process was proposed to identify sarcasm features. Five feature categories that can be extracted using natural language processing were considered. The best-performing features were then used as input for the second phase. In the second phase, a framework for sentiment analysis that considers sarcasm detection and classification was proposed. Results obtained demonstrate that the proposed features and framework are able to improve the performance of sentiment analysis.
Keyword:
HA29-32 Theory and method of social science statistics
;
QA299.6-433 Analysis
URL:
http://eprints.ums.edu.my/id/eprint/30793/2/Sarcasm%20Detection%20And%20Classification%20To%20Support%20Sentiment%20Analysis.pdf
http://eprints.ums.edu.my/id/eprint/30793/1/Sarcasm%20Detection%20And%20Classification%20To%20Support%20Sentiment%20Analysis%2024pages.pdf
http://eprints.ums.edu.my/id/eprint/30793/
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2
A Rule-Based Named-Entity Recognition for Malay Articles
Rayner Alfred
;
Leow, Ching Leong
;
Chin Kim On
. - : Springer-Verlag Berlin Heidelberg, 2013
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