Sarcasm Detection And Classification To Support Sentiment Analysis: A Study In Malay Social Media
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...
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| Main Author: | |
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| Format: | Research Report |
| Language: | English English |
| Published: |
2016
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| Online Access: | https://eprints.ums.edu.my/id/eprint/30793/1/Sarcasm%20Detection%20And%20Classification%20To%20Support%20Sentiment%20Analysis%2024pages.pdf https://eprints.ums.edu.my/id/eprint/30793/2/Sarcasm%20Detection%20And%20Classification%20To%20Support%20Sentiment%20Analysis.pdf https://eprints.ums.edu.my/id/eprint/30793/ |
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| Institution: | Universiti Malaysia Sabah |
| Language: | English English |
| Summary: | 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. |
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