relation: https://khub.utp.edu.my/scholars/15365/
title: Enhanced Sentiment Analysis Technique using Machine Learning (B.R.A.G.E technique)
creator: Mohamad, D.E.D.
creator: Hashim, A.S.
description: Sentiment Analysis have been the most growing topic in the recent years. It is the use of text analysis to examine the opinion or attitude towards a topic. In the past years, there have been a significant growth in the volume of research on Sentiment Analysis, on different detection level such as document level, sentence level and feature level. One of the famous existing sentiment analysis models is Naïve Bayes, a supervised machine learning model. In this study, we identified that the existing Naïve Bayes model trained and tested with incident/accident-related dataset gave an accuracy level of 71. Additionally, this study describes how the proposed B.R.A.GE. technique has slightly enhanced the sentiment analysis prediction accuracy using incident/accident-related dataset. In conclusion, the proposed B.R.A.G.E technique has not significantly improved the accuracy but hence could be further improvised. © 2021 IEEE.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2021
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Mohamad, D.E.D. and Hashim, A.S.  (2021) Enhanced Sentiment Analysis Technique using Machine Learning (B.R.A.G.E technique).  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126617274&doi=10.1109%2fICICyTA53712.2021.9689171&partnerID=40&md5=dac5233151643c1c5b44deb046734317
relation: 10.1109/ICICyTA53712.2021.9689171
identifier: 10.1109/ICICyTA53712.2021.9689171