Sentiment analysis of hotel reviews using Convolutional Neural Network / Sofea Aini Mohd Sufian

Tourism industry is one of the largest sectors and also one of the reasons to the development of hotels around the world. Most of them also use online booking system. Many online reviews are increasing every day because travellers are willing to share their experiences. This report presents the work...

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Main Author:	Mohd Sufian, Sofea Aini
Format:	Thesis
Language:	English
Published:	2021
Subjects:	Algebra Analysis Instruments and machines Algorithms
Online Access:	https://ir.uitm.edu.my/id/eprint/55656/1/55656.pdf
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id	my-uitm-ir.55656
record_format	uketd_dc
spelling	my-uitm-ir.556562022-02-07T08:30:48Z Sentiment analysis of hotel reviews using Convolutional Neural Network / Sofea Aini Mohd Sufian 2021-02 Mohd Sufian, Sofea Aini Algebra Electronic data processing. Maple (Computer file) Analysis Instruments and machines Electronic Computers. Computer Science Evolutionary programming (Computer science). Genetic algorithms Algorithms Tourism industry is one of the largest sectors and also one of the reasons to the development of hotels around the world. Most of them also use online booking system. Many online reviews are increasing every day because travellers are willing to share their experiences. This report presents the worked progress of sentiment analysis on hotel reviews using convolutional neural network. It is implemented to help users which is hotel’s staff that want to know more about their hotels from the reviews. The users face problems while reading the reviews because it consumes a lot of times and expressions of the sentences that are hard to understand whether it is positive or negative opinions since human language is complex. The traditional algorithm that been used a lot also reach a plateau of performance, with no room for improvement. So, the aim of this paper is to develop a prototype for hotel reviews using CNN Algorithm, to identify the requirements of CNN technique for text classification and also to evaluate the accuracy of CNN algorithm. The hotel reviews will be analysed using CNN text classification whether it is positive or negative sentiment. The experiment was doing by replacing the batch size, filter size, dropout and also the split of the data between training and testing numbers. It also used word2vec as word embedding. The result shows that CNN algorithm method can have high accuracy with more than 90% accuracy. The prototype also been implemented using CNN model to predict the sentiment on hotel review, hi conclusion, the CNN algorithm can be used as text classification as it gives a high accuracy. 2021-02 Thesis https://ir.uitm.edu.my/id/eprint/55656/ https://ir.uitm.edu.my/id/eprint/55656/1/55656.pdf text en public degree Universiti Teknologi MARA, Terengganu Faculty of Computer and Mathematical Sciences Jantan, Hamidah
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Jantan, Hamidah
topic	Algebra Algebra Analysis Instruments and machines Algebra Algebra Algorithms
spellingShingle	Algebra Algebra Analysis Instruments and machines Algebra Algebra Algorithms Mohd Sufian, Sofea Aini Sentiment analysis of hotel reviews using Convolutional Neural Network / Sofea Aini Mohd Sufian
description	Tourism industry is one of the largest sectors and also one of the reasons to the development of hotels around the world. Most of them also use online booking system. Many online reviews are increasing every day because travellers are willing to share their experiences. This report presents the worked progress of sentiment analysis on hotel reviews using convolutional neural network. It is implemented to help users which is hotel’s staff that want to know more about their hotels from the reviews. The users face problems while reading the reviews because it consumes a lot of times and expressions of the sentences that are hard to understand whether it is positive or negative opinions since human language is complex. The traditional algorithm that been used a lot also reach a plateau of performance, with no room for improvement. So, the aim of this paper is to develop a prototype for hotel reviews using CNN Algorithm, to identify the requirements of CNN technique for text classification and also to evaluate the accuracy of CNN algorithm. The hotel reviews will be analysed using CNN text classification whether it is positive or negative sentiment. The experiment was doing by replacing the batch size, filter size, dropout and also the split of the data between training and testing numbers. It also used word2vec as word embedding. The result shows that CNN algorithm method can have high accuracy with more than 90% accuracy. The prototype also been implemented using CNN model to predict the sentiment on hotel review, hi conclusion, the CNN algorithm can be used as text classification as it gives a high accuracy.
format	Thesis
qualification_level	Bachelor degree
author	Mohd Sufian, Sofea Aini
author_facet	Mohd Sufian, Sofea Aini
author_sort	Mohd Sufian, Sofea Aini
title	Sentiment analysis of hotel reviews using Convolutional Neural Network / Sofea Aini Mohd Sufian
title_short	Sentiment analysis of hotel reviews using Convolutional Neural Network / Sofea Aini Mohd Sufian
title_full	Sentiment analysis of hotel reviews using Convolutional Neural Network / Sofea Aini Mohd Sufian
title_fullStr	Sentiment analysis of hotel reviews using Convolutional Neural Network / Sofea Aini Mohd Sufian
title_full_unstemmed	Sentiment analysis of hotel reviews using Convolutional Neural Network / Sofea Aini Mohd Sufian
title_sort	sentiment analysis of hotel reviews using convolutional neural network / sofea aini mohd sufian
granting_institution	Universiti Teknologi MARA, Terengganu
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2021
url	https://ir.uitm.edu.my/id/eprint/55656/1/55656.pdf
_version_	1783734919721123840

Sentiment analysis of hotel reviews using Convolutional Neural Network / Sofea Aini Mohd Sufian

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