MELex: a new lexicon for sentiment analysis in mining public opinion of Malaysia affordable housing projects

Sentiment analysis has the potential as an analytical tool to understand the preferences of the public. It has become one of the most active and progressively popular areas in information retrieval and text mining. However, in the Malaysia context, the sentiment analysis is still limited due to the...

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Main Author:	Nurul Husna, Mahadzir
Format:	Thesis
Language:	eng eng eng
Published:	2020
Subjects:	QA299.6-433 Analysis
Online Access:	https://etd.uum.edu.my/8682/1/Deposit%20Permission_s900986.pdf https://etd.uum.edu.my/8682/2/s900986_01.pdf https://etd.uum.edu.my/8682/3/s900986_references.docx
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id	my-uum-etd.8682
record_format	uketd_dc
spelling	my-uum-etd.86822021-09-28T07:51:44Z MELex: a new lexicon for sentiment analysis in mining public opinion of Malaysia affordable housing projects 2020 Nurul Husna, Mahadzir Omar, Mohd Faizal Mohd Nawi, Mohd Nasrun Awang Had Salleh Graduate School of Arts & Sciences Awang Had Salleh Graduate School of Arts & Sciences QA299.6-433 Analysis Sentiment analysis has the potential as an analytical tool to understand the preferences of the public. It has become one of the most active and progressively popular areas in information retrieval and text mining. However, in the Malaysia context, the sentiment analysis is still limited due to the lack of sentiment lexicon. Thus, the focus of this study is to a new lexicon and enhance the classification accuracy of sentiment analysis in mining public opinion for Malaysia affordable housing project. The new lexicon for sentiment analysis is constructed by using a bilingual and domain-specific sentiment lexicon approach. A detailed review of existing approaches has been conducted and a new bilingual sentiment lexicon known as MELex (Malay-English Lexicon) has been generated. The developed approach is able to analyze text for two most widely used languages in Malaysia, Malay and English, with better accuracy. The process of constructing MELex involves three activities: seed words selection, polarity assignment and synonym expansions, with four different experiments have been implemented. It is evaluated based on the experimentation and case study approaches where PR1MA and PPAM are selected as case projects. Based on the comparative results over 2,230 testing data, the study reveals that the classification using MELex outperforms the existing approaches with the accuracy achieved for PR1MA and PPAM projects are 90.02% and 89.17%, respectively. This indicates the capabilities of MELex in classifying public sentiment towards PRIMA and PPAM housing projects. The study has shown promising and better results in property domain as compared to the previous research. Hence, the lexicon-based approach implemented in this study can reflect the reliability of the sentiment lexicon in classifying public sentiments. 2020 Thesis https://etd.uum.edu.my/8682/ https://etd.uum.edu.my/8682/1/Deposit%20Permission_s900986.pdf text eng staffonly https://etd.uum.edu.my/8682/2/s900986_01.pdf text eng public https://etd.uum.edu.my/8682/3/s900986_references.docx text eng public other doctoral Universiti Utara Malaysia
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng eng
advisor	Omar, Mohd Faizal Mohd Nawi, Mohd Nasrun
topic	QA299.6-433 Analysis
spellingShingle	QA299.6-433 Analysis Nurul Husna, Mahadzir MELex: a new lexicon for sentiment analysis in mining public opinion of Malaysia affordable housing projects
description	Sentiment analysis has the potential as an analytical tool to understand the preferences of the public. It has become one of the most active and progressively popular areas in information retrieval and text mining. However, in the Malaysia context, the sentiment analysis is still limited due to the lack of sentiment lexicon. Thus, the focus of this study is to a new lexicon and enhance the classification accuracy of sentiment analysis in mining public opinion for Malaysia affordable housing project. The new lexicon for sentiment analysis is constructed by using a bilingual and domain-specific sentiment lexicon approach. A detailed review of existing approaches has been conducted and a new bilingual sentiment lexicon known as MELex (Malay-English Lexicon) has been generated. The developed approach is able to analyze text for two most widely used languages in Malaysia, Malay and English, with better accuracy. The process of constructing MELex involves three activities: seed words selection, polarity assignment and synonym expansions, with four different experiments have been implemented. It is evaluated based on the experimentation and case study approaches where PR1MA and PPAM are selected as case projects. Based on the comparative results over 2,230 testing data, the study reveals that the classification using MELex outperforms the existing approaches with the accuracy achieved for PR1MA and PPAM projects are 90.02% and 89.17%, respectively. This indicates the capabilities of MELex in classifying public sentiment towards PRIMA and PPAM housing projects. The study has shown promising and better results in property domain as compared to the previous research. Hence, the lexicon-based approach implemented in this study can reflect the reliability of the sentiment lexicon in classifying public sentiments.
format	Thesis
qualification_name	other
qualification_level	Doctorate
author	Nurul Husna, Mahadzir
author_facet	Nurul Husna, Mahadzir
author_sort	Nurul Husna, Mahadzir
title	MELex: a new lexicon for sentiment analysis in mining public opinion of Malaysia affordable housing projects
title_short	MELex: a new lexicon for sentiment analysis in mining public opinion of Malaysia affordable housing projects
title_full	MELex: a new lexicon for sentiment analysis in mining public opinion of Malaysia affordable housing projects
title_fullStr	MELex: a new lexicon for sentiment analysis in mining public opinion of Malaysia affordable housing projects
title_full_unstemmed	MELex: a new lexicon for sentiment analysis in mining public opinion of Malaysia affordable housing projects
title_sort	melex: a new lexicon for sentiment analysis in mining public opinion of malaysia affordable housing projects
granting_institution	Universiti Utara Malaysia
granting_department	Awang Had Salleh Graduate School of Arts & Sciences
publishDate	2020
url	https://etd.uum.edu.my/8682/1/Deposit%20Permission_s900986.pdf https://etd.uum.edu.my/8682/2/s900986_01.pdf https://etd.uum.edu.my/8682/3/s900986_references.docx
_version_	1747828438595534848

MELex: a new lexicon for sentiment analysis in mining public opinion of Malaysia affordable housing projects

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