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: Kaur, W., Vimala, B.
Format: Conference or Workshop Item
Language:English
Published: 2016
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
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spelling my.um.eprints.155352016-01-20T04:22:33Z http://eprints.um.edu.my/15535/ Sentiment analysis technique: A look into support vector machine and naive bayes Kaur, W. Vimala, B. T Technology (General) TA Engineering (General). Civil engineering (General) 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. 2016-01 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.um.edu.my/15535/1/0001.pdf 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.
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
language English
topic T Technology (General)
TA Engineering (General). Civil engineering (General)
spellingShingle T Technology (General)
TA Engineering (General). Civil engineering (General)
Kaur, W.
Vimala, B.
Sentiment analysis technique: A look into support vector machine and naive bayes
description 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.
format Conference or Workshop Item
author Kaur, W.
Vimala, B.
author_facet Kaur, W.
Vimala, B.
author_sort Kaur, W.
title Sentiment analysis technique: A look into support vector machine and naive bayes
title_short Sentiment analysis technique: A look into support vector machine and naive bayes
title_full Sentiment analysis technique: A look into support vector machine and naive bayes
title_fullStr Sentiment analysis technique: A look into support vector machine and naive bayes
title_full_unstemmed Sentiment analysis technique: A look into support vector machine and naive bayes
title_sort sentiment analysis technique: a look into support vector machine and naive bayes
publishDate 2016
url http://eprints.um.edu.my/15535/1/0001.pdf
http://eprints.um.edu.my/15535/
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