eprintid: 15365
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/53/65
datestamp: 2023-11-10 03:29:59
lastmod: 2023-11-10 03:29:59
status_changed: 2023-11-10 01:59:18
type: conference_item
metadata_visibility: show
creators_name: Mohamad, D.E.D.
creators_name: Hashim, A.S.
title: Enhanced Sentiment Analysis Technique using Machine Learning (B.R.A.G.E technique)
ispublished: pub
keywords: Bayesian networks; Classifiers; Supervised learning, Analysis models; Analysis techniques; Detection levels; Feature level; Machine-learning; Naive bayes; Sentence features; Sentence level; Sentiment analysis; Supervised machine learning, Sentiment analysis
note: cited By 0; Conference of 2021 International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2021 ; Conference Date: 1 December 2021 Through 2 December 2021; Conference Code:176965
abstract: 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.
date: 2021
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126617274&doi=10.1109%2fICICyTA53712.2021.9689171&partnerID=40&md5=dac5233151643c1c5b44deb046734317
id_number: 10.1109/ICICyTA53712.2021.9689171
full_text_status: none
publication: 2021 International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2021
pagerange: 101-105
refereed: TRUE
isbn: 9781665417778
citation:   Mohamad, D.E.D. and Hashim, A.S.  (2021) Enhanced Sentiment Analysis Technique using Machine Learning (B.R.A.G.E technique).  In: UNSPECIFIED.