Cover Image

S-line centre automated beauty product review system by using keyword extraction and analysis extract from twitter / Amieza Kamelia Ahmad Kamarrudin

In recent year, the spectacular development of web technologies, lead to a large quantity of use generated information in online systems. This large amount of information on web platforms makes them viable to use as the data sources. The objective of this research is to develop a website that provid...

Full description

Saved in:
Bibliographic Details
Main Author: Ahmad Kamarrudin, Amieza Kamelia
Format: Thesis
Language:English
Published: 2017
Online Access:http://ir.uitm.edu.my/id/eprint/18104/2/TD_AMIEZA%20KAMELIA%20AHMAD%20KAMARRUDIN%20CS%2017_5.pdf
http://ir.uitm.edu.my/id/eprint/18104/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uitm.ir.18104
record_format eprints
spelling my.uitm.ir.181042019-02-27T07:33:20Z http://ir.uitm.edu.my/id/eprint/18104/ S-line centre automated beauty product review system by using keyword extraction and analysis extract from twitter / Amieza Kamelia Ahmad Kamarrudin Ahmad Kamarrudin, Amieza Kamelia In recent year, the spectacular development of web technologies, lead to a large quantity of use generated information in online systems. This large amount of information on web platforms makes them viable to use as the data sources. The objective of this research is to develop a website that provides polarity review for the product beauty by using sentiment analysis. There is several beauty product uses as the prototype for the research. Currently, S-Line Centre does not have it own websites to provide online view of the product for the company’s product. To overcome the problem, the objective has been discovered. This website can help the staff to provide product review based on customer opinion in Twitter. The tweet from the twitter is extracted, and the tweets are then analyzed by using sentiment analysis to provide the polarity of the product. The result from the project of the sentiment analysis is the negativity and the positivity of the tweets about the product. The website will show the most number of polarities that occurs. Text blob is used as the tool to generate the NLTK. To develop the project, the waterfall model methodology is used. The future enhancement for this project is to handle the limitations of the project which is to add more language to be detects. Other than that, this project can also be improved by adding new social network sites (SNS) other than twitter such as Instagram. This can provide a variety of people from different characteristic group. 2017 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/18104/2/TD_AMIEZA%20KAMELIA%20AHMAD%20KAMARRUDIN%20CS%2017_5.pdf Ahmad Kamarrudin, Amieza Kamelia (2017) S-line centre automated beauty product review system by using keyword extraction and analysis extract from twitter / Amieza Kamelia Ahmad Kamarrudin. Degree thesis, Universiti Teknologi MARA.
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
description In recent year, the spectacular development of web technologies, lead to a large quantity of use generated information in online systems. This large amount of information on web platforms makes them viable to use as the data sources. The objective of this research is to develop a website that provides polarity review for the product beauty by using sentiment analysis. There is several beauty product uses as the prototype for the research. Currently, S-Line Centre does not have it own websites to provide online view of the product for the company’s product. To overcome the problem, the objective has been discovered. This website can help the staff to provide product review based on customer opinion in Twitter. The tweet from the twitter is extracted, and the tweets are then analyzed by using sentiment analysis to provide the polarity of the product. The result from the project of the sentiment analysis is the negativity and the positivity of the tweets about the product. The website will show the most number of polarities that occurs. Text blob is used as the tool to generate the NLTK. To develop the project, the waterfall model methodology is used. The future enhancement for this project is to handle the limitations of the project which is to add more language to be detects. Other than that, this project can also be improved by adding new social network sites (SNS) other than twitter such as Instagram. This can provide a variety of people from different characteristic group.
format Thesis
author Ahmad Kamarrudin, Amieza Kamelia
spellingShingle Ahmad Kamarrudin, Amieza Kamelia
S-line centre automated beauty product review system by using keyword extraction and analysis extract from twitter / Amieza Kamelia Ahmad Kamarrudin
author_facet Ahmad Kamarrudin, Amieza Kamelia
author_sort Ahmad Kamarrudin, Amieza Kamelia
title S-line centre automated beauty product review system by using keyword extraction and analysis extract from twitter / Amieza Kamelia Ahmad Kamarrudin
title_short S-line centre automated beauty product review system by using keyword extraction and analysis extract from twitter / Amieza Kamelia Ahmad Kamarrudin
title_full S-line centre automated beauty product review system by using keyword extraction and analysis extract from twitter / Amieza Kamelia Ahmad Kamarrudin
title_fullStr S-line centre automated beauty product review system by using keyword extraction and analysis extract from twitter / Amieza Kamelia Ahmad Kamarrudin
title_full_unstemmed S-line centre automated beauty product review system by using keyword extraction and analysis extract from twitter / Amieza Kamelia Ahmad Kamarrudin
title_sort s-line centre automated beauty product review system by using keyword extraction and analysis extract from twitter / amieza kamelia ahmad kamarrudin
publishDate 2017
url http://ir.uitm.edu.my/id/eprint/18104/2/TD_AMIEZA%20KAMELIA%20AHMAD%20KAMARRUDIN%20CS%2017_5.pdf
http://ir.uitm.edu.my/id/eprint/18104/
_version_ 1685649035841503232
score 13.211869

Similar Items