Classification and visualization of E-commerce product reviews comparison using support vector machine / Nuwairah Aimi Ahmad Kushairi, Khyrina Airin Fariza Abu Samah and Nurul Atirah Ahmad

E-commerce is significantly growing as a platform for online shopping, offering convenience and costsaving benefits. Especially in Malaysia, Shopee is one of the leading e-commerce platforms. These days, online product reviews play a crucial role in influencing consumer behaviour by building trust,...

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Main Authors: Ahmad Kushairi, Nuwairah Aimi, Abu Samah, Airin Fariza, Ahmad, Nurul Atirah
Format: Book Section
Language:English
Published: Faculty of Computer and Mathematical Sciences 2023
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/94178/1/94178.pdf
https://ir.uitm.edu.my/id/eprint/94178/
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spelling my.uitm.ir.941782024-05-02T03:15:42Z https://ir.uitm.edu.my/id/eprint/94178/ Classification and visualization of E-commerce product reviews comparison using support vector machine / Nuwairah Aimi Ahmad Kushairi, Khyrina Airin Fariza Abu Samah and Nurul Atirah Ahmad Ahmad Kushairi, Nuwairah Aimi Abu Samah, Airin Fariza Ahmad, Nurul Atirah Integer programming E-commerce is significantly growing as a platform for online shopping, offering convenience and costsaving benefits. Especially in Malaysia, Shopee is one of the leading e-commerce platforms. These days, online product reviews play a crucial role in influencing consumer behaviour by building trust, identifying customer needs, and improving satisfaction. 181 out of a 186 respondents questionnaire survey agreed that they rely on product reviews before purchasing any product. Nevertheless, 179 respondents agreed that not all product reviews are helpful when shopping online. It becomes time-consuming to read through the reviews, especially when it is not product related. Moreover, an abundance of reviews can lead to information overload, which exhausts customers to decide. Therefore, this study aims to classify the comparison of useful and not useful product reviews from Shopee using Support Vector Machine (SVM) and visualize the comparison. Users can enter up to six product links, and the system will classify reviews based on review text, star rating, duplicated spam, and sentiment score. Testing showed 96.8% accuracy and passed all functionality test cases. Mann-Whitney U Test obtained a p-value of 0.008, indicating a significant difference in evaluation time over manual evaluation, proving its potential in aiding purchase decisions. Faculty of Computer and Mathematical Sciences 2023 Book Section NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/94178/1/94178.pdf Classification and visualization of E-commerce product reviews comparison using support vector machine / Nuwairah Aimi Ahmad Kushairi, Khyrina Airin Fariza Abu Samah and Nurul Atirah Ahmad. (2023) In: International Jasin Multimedia & Computer Science Invention and Innovation Exhibition (i-JaMCSIIX 2023). Faculty of Computer and Mathematical Sciences, Kampus Jasin, p. 72. (Submitted)
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Integer programming
spellingShingle Integer programming
Ahmad Kushairi, Nuwairah Aimi
Abu Samah, Airin Fariza
Ahmad, Nurul Atirah
Classification and visualization of E-commerce product reviews comparison using support vector machine / Nuwairah Aimi Ahmad Kushairi, Khyrina Airin Fariza Abu Samah and Nurul Atirah Ahmad
description E-commerce is significantly growing as a platform for online shopping, offering convenience and costsaving benefits. Especially in Malaysia, Shopee is one of the leading e-commerce platforms. These days, online product reviews play a crucial role in influencing consumer behaviour by building trust, identifying customer needs, and improving satisfaction. 181 out of a 186 respondents questionnaire survey agreed that they rely on product reviews before purchasing any product. Nevertheless, 179 respondents agreed that not all product reviews are helpful when shopping online. It becomes time-consuming to read through the reviews, especially when it is not product related. Moreover, an abundance of reviews can lead to information overload, which exhausts customers to decide. Therefore, this study aims to classify the comparison of useful and not useful product reviews from Shopee using Support Vector Machine (SVM) and visualize the comparison. Users can enter up to six product links, and the system will classify reviews based on review text, star rating, duplicated spam, and sentiment score. Testing showed 96.8% accuracy and passed all functionality test cases. Mann-Whitney U Test obtained a p-value of 0.008, indicating a significant difference in evaluation time over manual evaluation, proving its potential in aiding purchase decisions.
format Book Section
author Ahmad Kushairi, Nuwairah Aimi
Abu Samah, Airin Fariza
Ahmad, Nurul Atirah
author_facet Ahmad Kushairi, Nuwairah Aimi
Abu Samah, Airin Fariza
Ahmad, Nurul Atirah
author_sort Ahmad Kushairi, Nuwairah Aimi
title Classification and visualization of E-commerce product reviews comparison using support vector machine / Nuwairah Aimi Ahmad Kushairi, Khyrina Airin Fariza Abu Samah and Nurul Atirah Ahmad
title_short Classification and visualization of E-commerce product reviews comparison using support vector machine / Nuwairah Aimi Ahmad Kushairi, Khyrina Airin Fariza Abu Samah and Nurul Atirah Ahmad
title_full Classification and visualization of E-commerce product reviews comparison using support vector machine / Nuwairah Aimi Ahmad Kushairi, Khyrina Airin Fariza Abu Samah and Nurul Atirah Ahmad
title_fullStr Classification and visualization of E-commerce product reviews comparison using support vector machine / Nuwairah Aimi Ahmad Kushairi, Khyrina Airin Fariza Abu Samah and Nurul Atirah Ahmad
title_full_unstemmed Classification and visualization of E-commerce product reviews comparison using support vector machine / Nuwairah Aimi Ahmad Kushairi, Khyrina Airin Fariza Abu Samah and Nurul Atirah Ahmad
title_sort classification and visualization of e-commerce product reviews comparison using support vector machine / nuwairah aimi ahmad kushairi, khyrina airin fariza abu samah and nurul atirah ahmad
publisher Faculty of Computer and Mathematical Sciences
publishDate 2023
url https://ir.uitm.edu.my/id/eprint/94178/1/94178.pdf
https://ir.uitm.edu.my/id/eprint/94178/
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score 13.211869