VISA: A visual sentiment analysis system

Abstract

Sentiment plays a critical role in many information-centric business scenarios. The opinion mining methods proposed in the recent decade have formed a solid foundation to investigate the sentiment analysis tasks, but are often too complicated and scattered to serve the needs of real customers. We introduce the VISA system in this paper, which applies the visualization technology to synthesize the sentiment analysis results and present to the end user in an interactive manner. VISA builds on the generic sentiment tuple based data model and consumes the different facets of sentiment data with coordinated multiple views, hence is scalable to work with most of existing sentiment analysis engines on various application domains. We showcase the usage of VISA in a real world example and demonstrate the system's effectiveness through the user trail in finding an appropriate hotel for his family trip. © 2012 ACM.