With the growth of user generated contents (UGC), it is important to know consumers' opinions about features or deficiencies of products quickly. Such information is important not only for companies, but also for consumers. Keyword-based visualization and clustering are effective methods to observe summary of opinions. In order to decrease users' effort in examining vast amount of UGC, we proposed an interactive visualization system that presents sentiment words with aspects based on natural language processing and sentiment lexicon. This paper also proposes to apply latent Dirichlet allocation (LDA) to cluster reviews into several topics in order to improve understandability of visualization. This paper explains the developed system with case studies.
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