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Item

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Analyzing Sentiment Level of Social Media Data Based on SVM and Naïve Bayes Algorithm

http://hdl.handle.net/20.500.12678/0000007365
902c2751-50ec-4d2e-b21d-e1fa81d00219
abaaa88e-7cd0-4869-82dd-9551b967825d
None
Name / File License Actions
8. 8. Analyzing Sentiment Level of Social Media Data(Miyazaki ICBDL) (Phyu Thwe).pdf (354 KB)
Publication type
Conference paper
Upload type
Publication
Title
Title Analyzing Sentiment Level of Social Media Data Based on SVM and Naïve Bayes Algorithm
Language en
Publication date 2018-05-14
Authors
Hsu Wai Naing
Phyu Thwe
Aye Chan Mon
Naw Naw
Description
The system performs classification by combining Naïve Bayes (NB) and Support Vector Machine (SVM). The system is intended to measure the impact of ASEAN citizens’ social media based on their usage behavior. The system is developed for analyzing National Educational Rate, Busi-ness Rate and Crime Rate occurred in Malaysia, Singapore, Vietnam and our country, Myanmar.
Keywords
Opinion Mining, Sentiment Analysis, Twitter, Support Vector Machine (SVM), Naïve Byes (NB), Text Classification
Identifier http://www.cc.miyazaki-u.ac.jp/icbdm/
Conference papers
ICBDL 2018
14-05-2018
1st International Conference on Big Data Analysis and Deep Learning
Japan
http://www.cc.miyazaki-u.ac.jp/icbdm/
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