Abstract
This paper presents strategy to classify tweets sentiment using Naive Bayes techniques based on trainers' perception into three categories; positive, negative or neutral. 50 tweets of 'Malaysia' and 'Maybank' keywords were selected from Twitter for perception training. In this study, there were 27 trainers participated. Each trainer was asked to classify the sentiment of 25 tweets of each keyword. Results from the classification training was then be used as the input for Naive Bayes training for the remaining 25 tweets. The trainers were then asked to validate the results of sentiment classification by the Naive Bayes technique. The accuracy of this study is 90% ± 14% measured by total number of correct per total classified tweets.
| Original language | English |
|---|---|
| Title of host publication | 2015 IEEE Conference on e-Learning, e-Management and e-Services, IC3e 2015 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 187-189 |
| Number of pages | 3 |
| ISBN (Electronic) | 9781467394376 |
| DOIs | |
| Publication status | Published - 08 Feb 2016 |
| Event | IEEE Conference on e-Learning, e-Management and e-Services, IC3e 2015 - Melaka, Malaysia Duration: 24 Aug 2015 → 26 Aug 2015 |
Publication series
| Name | 2015 IEEE Conference on e-Learning, e-Management and e-Services, IC3e 2015 |
|---|
Other
| Other | IEEE Conference on e-Learning, e-Management and e-Services, IC3e 2015 |
|---|---|
| Country | Malaysia |
| City | Melaka |
| Period | 24/08/15 → 26/08/15 |
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All Science Journal Classification (ASJC) codes
- Education
- Computer Networks and Communications
- Computer Science Applications
Cite this
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Twitter sentiment classification using Naive Bayes based on trainer perception. / Ibrahim, Mohd Naim Mohd; Mohd Yusoff, Mohd Zaliman.
2015 IEEE Conference on e-Learning, e-Management and e-Services, IC3e 2015. Institute of Electrical and Electronics Engineers Inc., 2016. p. 187-189 7403510 (2015 IEEE Conference on e-Learning, e-Management and e-Services, IC3e 2015).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Twitter sentiment classification using Naive Bayes based on trainer perception
AU - Ibrahim, Mohd Naim Mohd
AU - Mohd Yusoff, Mohd Zaliman
PY - 2016/2/8
Y1 - 2016/2/8
N2 - This paper presents strategy to classify tweets sentiment using Naive Bayes techniques based on trainers' perception into three categories; positive, negative or neutral. 50 tweets of 'Malaysia' and 'Maybank' keywords were selected from Twitter for perception training. In this study, there were 27 trainers participated. Each trainer was asked to classify the sentiment of 25 tweets of each keyword. Results from the classification training was then be used as the input for Naive Bayes training for the remaining 25 tweets. The trainers were then asked to validate the results of sentiment classification by the Naive Bayes technique. The accuracy of this study is 90% ± 14% measured by total number of correct per total classified tweets.
AB - This paper presents strategy to classify tweets sentiment using Naive Bayes techniques based on trainers' perception into three categories; positive, negative or neutral. 50 tweets of 'Malaysia' and 'Maybank' keywords were selected from Twitter for perception training. In this study, there were 27 trainers participated. Each trainer was asked to classify the sentiment of 25 tweets of each keyword. Results from the classification training was then be used as the input for Naive Bayes training for the remaining 25 tweets. The trainers were then asked to validate the results of sentiment classification by the Naive Bayes technique. The accuracy of this study is 90% ± 14% measured by total number of correct per total classified tweets.
UR - http://www.scopus.com/inward/record.url?scp=84963830519&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84963830519&partnerID=8YFLogxK
U2 - 10.1109/IC3e.2015.7403510
DO - 10.1109/IC3e.2015.7403510
M3 - Conference contribution
T3 - 2015 IEEE Conference on e-Learning, e-Management and e-Services, IC3e 2015
SP - 187
EP - 189
BT - 2015 IEEE Conference on e-Learning, e-Management and e-Services, IC3e 2015
PB - Institute of Electrical and Electronics Engineers Inc.
ER -