Sentiment analysis technique: A look into support vector machine and naive bayes
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...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2016
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/15535/1/0001.pdf http://eprints.um.edu.my/15535/ |
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| Institution: | Universiti Malaya |
| Language: | English |
| Summary: | 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. |
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