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Twitter sentiment classification using Naive Bayes based on trainer perception

E-learning; Social networking (online); Supervised learning; Malaysia; Naive bayes; Sentiment classification; Three categories; Classifiers

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Bibliographic Details
Main Authors: Ibrahim M.N.M., Yusoff M.Z.M.
Other Authors: 56258624800
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers Inc. 2023
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spelling my.uniten.dspace-228452023-05-29T14:12:40Z Twitter sentiment classification using Naive Bayes based on trainer perception Ibrahim M.N.M. Yusoff M.Z.M. 56258624800 22636590200 E-learning; Social networking (online); Supervised learning; Malaysia; Naive bayes; Sentiment classification; Three categories; Classifiers 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. � 2015 IEEE. Final 2023-05-29T06:12:40Z 2023-05-29T06:12:40Z 2016 Conference Paper 10.1109/IC3e.2015.7403510 2-s2.0-84963830519 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84963830519&doi=10.1109%2fIC3e.2015.7403510&partnerID=40&md5=80401f05ac52e14f06aa9ceffcebd610 https://irepository.uniten.edu.my/handle/123456789/22845 7403510 187 189 Institute of Electrical and Electronics Engineers Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description E-learning; Social networking (online); Supervised learning; Malaysia; Naive bayes; Sentiment classification; Three categories; Classifiers
author2 56258624800
author_facet 56258624800
Ibrahim M.N.M.
Yusoff M.Z.M.
format Conference Paper
author Ibrahim M.N.M.
Yusoff M.Z.M.
spellingShingle Ibrahim M.N.M.
Yusoff M.Z.M.
Twitter sentiment classification using Naive Bayes based on trainer perception
author_sort Ibrahim M.N.M.
title Twitter sentiment classification using Naive Bayes based on trainer perception
title_short Twitter sentiment classification using Naive Bayes based on trainer perception
title_full Twitter sentiment classification using Naive Bayes based on trainer perception
title_fullStr Twitter sentiment classification using Naive Bayes based on trainer perception
title_full_unstemmed Twitter sentiment classification using Naive Bayes based on trainer perception
title_sort twitter sentiment classification using naive bayes based on trainer perception
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2023
_version_ 1806427929607929856
score 13.214268

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