Developing a Sentiment Polarity Visualization System for Local Event Information Analysis

Abstract

It is important to analyze the reputation or demands for a local event, such as a school festival. The aim of this research is to develop a system that enables its users to collect and to analyze local event information from social media. In this paper, we have shown the over view and described the implementation of the proposed system. Our system extracts tweets by sentiment polarity classification and visualizes them. In this paper, we described the performance of the sentiment polarity classification and showed that the system is efficient for coordinating tweets. We collected tweets about a local event and classified them manually. The sentiment polarity classification of our system was evaluated by comparing it with the manually classified tweets. We also discussed an example of local event analysis using our system and showed the efficiency of our system.