Sentiment analysis on national cultural tourism using Linear Support Vector Machine (LSVM) / Nur Haida Hanna Samsuddin

Nowadays, sentiment analysis plays a big role for many industries especially it is something related with feedback or reviews from people in cyberspace. People reviewed some products, places and others by expressing their opinion or emotion into sentences. This leads to the problem of understanding...

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Main Author:	Samsuddin, Nur Haida Hanna
Format:	Thesis
Language:	English
Published:	2020
Subjects:	Mathematical statistics Probabilities Data processing Instruments and machines Data mining
Online Access:	https://ir.uitm.edu.my/id/eprint/55332/1/55332.pdf
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id	my-uitm-ir.55332
record_format	uketd_dc
spelling	my-uitm-ir.553322022-01-26T02:41:26Z Sentiment analysis on national cultural tourism using Linear Support Vector Machine (LSVM) / Nur Haida Hanna Samsuddin 2020-08 Samsuddin, Nur Haida Hanna Mathematical statistics. Probabilities Data processing Instruments and machines Electronic Computers. Computer Science Data mining Nowadays, sentiment analysis plays a big role for many industries especially it is something related with feedback or reviews from people in cyberspace. People reviewed some products, places and others by expressing their opinion or emotion into sentences. This leads to the problem of understanding the meaning behind the texts and difficult to discover the sentiment polarity of certain words. Cultural tourism in Malaysia is lacking in terms of their promotional activities and any related authorities in the tourism industry often overlooked the reviews from tourists about cultural heritage destinations. Moreover, negative reviews may impact the national tourism. This study will perform sentiment analysis on national cultural tourism of tourists reviews on TripAdvisor website. The study will identify sentiment analysis tasks based on classification model. A classifier will be designed and developed which is Linear Support Vector Machine (LSVM). Lastly, the accuracy of the proposed classifier will be tested. Therefore, the chosen technique is classification and the algorithm that will be applied in the classification process is Linear Support Vector Machines (LSVM). The output will be the accuracy of the LSVM model and the visualization of sentiment analysis of new data that user will choose in the prototype. The accuracy achieved from the project is 80%. The classifier is claimed to be bad classifier because AUC-ROC gained from the experiment is 0.5. In future, it is recommended to experiment with different algorithm or kernel of Support Vector Machine. The volume of data should be large as it can generate better result of classification method. 2020-08 Thesis https://ir.uitm.edu.my/id/eprint/55332/ https://ir.uitm.edu.my/id/eprint/55332/1/55332.pdf text en public degree Universiti Teknologi MARA, Terengganu Faculty of Computer and Mathematical Sciences Mohamad, Norizan
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Mohamad, Norizan
topic	Mathematical statistics Probabilities Data processing Instruments and machines Mathematical statistics Probabilities Data mining
spellingShingle	Mathematical statistics Probabilities Data processing Instruments and machines Mathematical statistics Probabilities Data mining Samsuddin, Nur Haida Hanna Sentiment analysis on national cultural tourism using Linear Support Vector Machine (LSVM) / Nur Haida Hanna Samsuddin
description	Nowadays, sentiment analysis plays a big role for many industries especially it is something related with feedback or reviews from people in cyberspace. People reviewed some products, places and others by expressing their opinion or emotion into sentences. This leads to the problem of understanding the meaning behind the texts and difficult to discover the sentiment polarity of certain words. Cultural tourism in Malaysia is lacking in terms of their promotional activities and any related authorities in the tourism industry often overlooked the reviews from tourists about cultural heritage destinations. Moreover, negative reviews may impact the national tourism. This study will perform sentiment analysis on national cultural tourism of tourists reviews on TripAdvisor website. The study will identify sentiment analysis tasks based on classification model. A classifier will be designed and developed which is Linear Support Vector Machine (LSVM). Lastly, the accuracy of the proposed classifier will be tested. Therefore, the chosen technique is classification and the algorithm that will be applied in the classification process is Linear Support Vector Machines (LSVM). The output will be the accuracy of the LSVM model and the visualization of sentiment analysis of new data that user will choose in the prototype. The accuracy achieved from the project is 80%. The classifier is claimed to be bad classifier because AUC-ROC gained from the experiment is 0.5. In future, it is recommended to experiment with different algorithm or kernel of Support Vector Machine. The volume of data should be large as it can generate better result of classification method.
format	Thesis
qualification_level	Bachelor degree
author	Samsuddin, Nur Haida Hanna
author_facet	Samsuddin, Nur Haida Hanna
author_sort	Samsuddin, Nur Haida Hanna
title	Sentiment analysis on national cultural tourism using Linear Support Vector Machine (LSVM) / Nur Haida Hanna Samsuddin
title_short	Sentiment analysis on national cultural tourism using Linear Support Vector Machine (LSVM) / Nur Haida Hanna Samsuddin
title_full	Sentiment analysis on national cultural tourism using Linear Support Vector Machine (LSVM) / Nur Haida Hanna Samsuddin
title_fullStr	Sentiment analysis on national cultural tourism using Linear Support Vector Machine (LSVM) / Nur Haida Hanna Samsuddin
title_full_unstemmed	Sentiment analysis on national cultural tourism using Linear Support Vector Machine (LSVM) / Nur Haida Hanna Samsuddin
title_sort	sentiment analysis on national cultural tourism using linear support vector machine (lsvm) / nur haida hanna samsuddin
granting_institution	Universiti Teknologi MARA, Terengganu
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2020
url	https://ir.uitm.edu.my/id/eprint/55332/1/55332.pdf
_version_	1783734913407647744

Sentiment analysis on national cultural tourism using Linear Support Vector Machine (LSVM) / Nur Haida Hanna Samsuddin

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