Sentiment Analysis on Students’ Satisfaction Towards University - Mohd Idrus, Muhammad Faris (IRC, 2020)
The arrival of social media platforms has changed the way people express themselves. They share their opinions or perceptions towards products and services online and in real-time. With the abundance of publicly available data, it could be used to perform sentiment analysis that has the capability to classify each data into positive, negative and neutral sentiment. Developing a sentiment analysis model to analyse how people talk about UTP brands could enhance their marketing strategy. Issues related to facilities and services such as poor facilities, expensive annual fees, expensive cafeteria food would be a key highlight to this project. Several scopes has been identified for this project development. Besides, this paper reports on methodology that would be implemented for developing sentiment analysis model and it would adopt waterfall model. Sentiment analysis requires dataset to undergo data preprocessing and data classification. Due to its capability to outperform other classifier, Naïve Bayes classifier has been chosen to perform the classification process. In the end, data would be presented in a form of smart chart.