Kaur, W. and Vimala, B. (2016) Sentiment analysis technique: A look into support vector machine and naive bayes. In: International Conference on IT, Mechanical & Communication Engineering (ICIME 2016), 02-03 January 2016, Pattaya, Thailand.
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Abstract
Sentiment Analysis and opinion mining aims to analyze sentiments, opinions, emotions etc. towards products, services or current topics. There are various approaches applied to mine the sentiments portrayed. Supervised machine learning is one such approach that is generally applied. The aim of this paper is to investigate the current methods used to perform sentiment analysis by reviewing and comparing recently published research. The findings are discussed in hope that it would help future researchers to gain an understanding of a possible method they could adopt or even come up with a new approach to better mine sentiments from big data that is tailored to suit the need of their data source.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | Sentiment analysis, Naive Bayes, support vector machine, supervised machine learning |
| Subjects: | T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) |
| Divisions: | Faculty of Computer Science & Information Technology |
| Depositing User: | Mr. Mohd Safri |
| Date Deposited: | 20 Jan 2016 04:22 |
| Last Modified: | 20 Jan 2016 04:22 |
| URI: | http://eprints.um.edu.my/id/eprint/15535 |
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