Subjectivity analysis using machine learning algorithm

This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016.

Opis bibliograficzny
Główni autorzy:	Ahmed, Erfan, Azad, Muhitun, Islam, Md. Tanzim, Sazzad, Md. Asad Uzzaman
Kolejni autorzy:	Ali, Dr. Md. Haider
Format:	Praca dyplomowa
Język:	English
Wydane:	BRAC University 2017
Hasła przedmiotowe:	Machine learning algorithm Rotten tomato SVM Subjectivity analysis
Dostęp online:	http://hdl.handle.net/10361/7624

id	10361-7624
record_format	dspace
spelling	10361-76242022-01-26T10:23:15Z Subjectivity analysis using machine learning algorithm Ahmed, Erfan Azad, Muhitun Islam, Md. Tanzim Sazzad, Md. Asad Uzzaman Ali, Dr. Md. Haider Islam, Samiul Department of Computer Science and Engineering, BRAC University Machine learning algorithm Rotten tomato SVM Subjectivity analysis This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016. Cataloged from PDF version of thesis report. Includes bibliographical references (page 83-85). This paper investigates a new approach of finding sentence level subjectivity analysis using different machine learning algorithms. Along with subjectivity analysis sentiment analysis has also been shown separately in this work. Three different machine learning algorithms - SVM, Naïve Bayes and MLP have been used both for subjectivity and sentiment analysis. Moreover four different classifiers of Naïve Bayes and three different kernels of SVM have been used in this work to analyze the difference in accuracy as well as to find the best outcome among all the experiments. For subjectivity analysis rotten tomato imdb movie review [1] dataset has being used and for sentiment analysis acl imdb movie review [2] dataset has been used. Lastly, the impact of stop words and number of attributes in accuracy both for subjectivity and sentiment analysis has also been illustrated. Erfan Ahmed Muhitun Azad Md. Tanzim Islam Md. Asad Uzzaman Sazzad B. Computer Science and Engineering 2017-01-19T06:46:26Z 2017-01-19T06:46:26Z 2016 2016 Thesis ID 13101139 ID 13101073 ID 13101158 ID 13101152 http://hdl.handle.net/10361/7624 en BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 85 pages application/pdf BRAC University
institution	Brac University
collection	Institutional Repository
language	English
topic	Machine learning algorithm Rotten tomato SVM Subjectivity analysis
spellingShingle	Machine learning algorithm Rotten tomato SVM Subjectivity analysis Ahmed, Erfan Azad, Muhitun Islam, Md. Tanzim Sazzad, Md. Asad Uzzaman Subjectivity analysis using machine learning algorithm
description	This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016.
author2	Ali, Dr. Md. Haider
author_facet	Ali, Dr. Md. Haider Ahmed, Erfan Azad, Muhitun Islam, Md. Tanzim Sazzad, Md. Asad Uzzaman
format	Thesis
author	Ahmed, Erfan Azad, Muhitun Islam, Md. Tanzim Sazzad, Md. Asad Uzzaman
author_sort	Ahmed, Erfan
title	Subjectivity analysis using machine learning algorithm
title_short	Subjectivity analysis using machine learning algorithm
title_full	Subjectivity analysis using machine learning algorithm
title_fullStr	Subjectivity analysis using machine learning algorithm
title_full_unstemmed	Subjectivity analysis using machine learning algorithm
title_sort	subjectivity analysis using machine learning algorithm
publisher	BRAC University
publishDate	2017
url	http://hdl.handle.net/10361/7624
work_keys_str_mv	AT ahmederfan subjectivityanalysisusingmachinelearningalgorithm AT azadmuhitun subjectivityanalysisusingmachinelearningalgorithm AT islammdtanzim subjectivityanalysisusingmachinelearningalgorithm AT sazzadmdasaduzzaman subjectivityanalysisusingmachinelearningalgorithm
_version_	1814309757980246016

Subjectivity analysis using machine learning algorithm

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