Sentiment analysis for malay newspaper (SAMNews) using negative selection algorithm / Nur Amalina Redzuan

Newspapers express sentiments during reporting on recent events every day. It also can be known as a new domain in textual type for sentiment analysis that deals with many suggestions. The newspaper is documented in long sentences but the contents that express the sentiment is compressed and clearly...

Full description

Saved in:

Bibliographic Details
Main Author:	Redzuan, Nur Amalina
Format:	Thesis
Language:	English
Published:	2013
Subjects:	Analysis Algorithms
Online Access:	https://ir.uitm.edu.my/id/eprint/35332/1/35332.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-uitm-ir.35332
record_format	uketd_dc
spelling	my-uitm-ir.353322020-10-20T07:07:24Z Sentiment analysis for malay newspaper (SAMNews) using negative selection algorithm / Nur Amalina Redzuan 2013-01 Redzuan, Nur Amalina Analysis Electronic Computers. Computer Science Algorithms Newspapers express sentiments during reporting on recent events every day. It also can be known as a new domain in textual type for sentiment analysis that deals with many suggestions. The newspaper is documented in long sentences but the contents that express the sentiment is compressed and clearly understand by human. However, for the machine learning text representation it cause some problems because of the noisy text. As the solution, this project is conducted on the purpose to determine the polarity of the sentiment in the newspapers sentences. This project is implemented based on five phases in methodology part which consists of background study, data collection and preparation, prototype design, prototype development and evaluation and dociunentation. Sentiment Analysis for Malay Newspaper (SAMNews) is constructed using the negative selection algorithm which is able to classify the sentiment in newspaper’s sentences into the polarity (positive, negative or neutral) automatically repose on detectors word. The sentiment analysis in this project utilized 1000 newspaper’s sentences for the training and classification phase and testing data to evaluate the average of accurateness. The evaluation is made on three experiments which in Experiment I used 700 newspaper’s sentences as the training data and 300 newspaper’s sentences as the testing data. The accuracy of this experiment is about 59.99%. In Experiment II, 800 newspaper’s sentences and 200 newspaper’s sentences are used as the training data and testing data. The accuracy of tins experiment is increased about 58.58%. While in Experiment III used 900 newspaper’s sentences as the training data and 100 newspaper’s sentences as the testing data and the accuracy is unproved to 65.81%. In future, a comparative study on Artificial Immune System and other techniques or algorithms can be carried out to enhance the performance of the classification model. 2013-01 Thesis https://ir.uitm.edu.my/id/eprint/35332/ https://ir.uitm.edu.my/id/eprint/35332/1/35332.pdf text en public degree Universiti Teknologi MARA Terengganu Faculty of Computer & Mathematical Sciences Isa, Norul Hidayah Jantan, Hamidah
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Isa, Norul Hidayah Jantan, Hamidah
topic	Analysis Analysis Algorithms
spellingShingle	Analysis Analysis Algorithms Redzuan, Nur Amalina Sentiment analysis for malay newspaper (SAMNews) using negative selection algorithm / Nur Amalina Redzuan
description	Newspapers express sentiments during reporting on recent events every day. It also can be known as a new domain in textual type for sentiment analysis that deals with many suggestions. The newspaper is documented in long sentences but the contents that express the sentiment is compressed and clearly understand by human. However, for the machine learning text representation it cause some problems because of the noisy text. As the solution, this project is conducted on the purpose to determine the polarity of the sentiment in the newspapers sentences. This project is implemented based on five phases in methodology part which consists of background study, data collection and preparation, prototype design, prototype development and evaluation and dociunentation. Sentiment Analysis for Malay Newspaper (SAMNews) is constructed using the negative selection algorithm which is able to classify the sentiment in newspaper’s sentences into the polarity (positive, negative or neutral) automatically repose on detectors word. The sentiment analysis in this project utilized 1000 newspaper’s sentences for the training and classification phase and testing data to evaluate the average of accurateness. The evaluation is made on three experiments which in Experiment I used 700 newspaper’s sentences as the training data and 300 newspaper’s sentences as the testing data. The accuracy of this experiment is about 59.99%. In Experiment II, 800 newspaper’s sentences and 200 newspaper’s sentences are used as the training data and testing data. The accuracy of tins experiment is increased about 58.58%. While in Experiment III used 900 newspaper’s sentences as the training data and 100 newspaper’s sentences as the testing data and the accuracy is unproved to 65.81%. In future, a comparative study on Artificial Immune System and other techniques or algorithms can be carried out to enhance the performance of the classification model.
format	Thesis
qualification_level	Bachelor degree
author	Redzuan, Nur Amalina
author_facet	Redzuan, Nur Amalina
author_sort	Redzuan, Nur Amalina
title	Sentiment analysis for malay newspaper (SAMNews) using negative selection algorithm / Nur Amalina Redzuan
title_short	Sentiment analysis for malay newspaper (SAMNews) using negative selection algorithm / Nur Amalina Redzuan
title_full	Sentiment analysis for malay newspaper (SAMNews) using negative selection algorithm / Nur Amalina Redzuan
title_fullStr	Sentiment analysis for malay newspaper (SAMNews) using negative selection algorithm / Nur Amalina Redzuan
title_full_unstemmed	Sentiment analysis for malay newspaper (SAMNews) using negative selection algorithm / Nur Amalina Redzuan
title_sort	sentiment analysis for malay newspaper (samnews) using negative selection algorithm / nur amalina redzuan
granting_institution	Universiti Teknologi MARA Terengganu
granting_department	Faculty of Computer & Mathematical Sciences
publishDate	2013
url	https://ir.uitm.edu.my/id/eprint/35332/1/35332.pdf
_version_	1783734299153924096

Sentiment analysis for malay newspaper (SAMNews) using negative selection algorithm / Nur Amalina Redzuan

Similar Items