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 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.