Clustered Layout Word Cloud for User Generated Review

User generated reviews, like those found on Yelp, have become important reference material in casual decision making, like dining, shopping and entertainment. However, very large amounts of reviews make the review reading process time consuming. A text visualization could be used to speed up review reading process. In this paper, we present the clustered layout word cloud; a text visualization that would assist in making decision quicker based on user generated reviews. We used a natural language processing approach, called grammatical dependency parsing, to analyze user generated review content and created a semantic graph. A force-directed graph layout was applied to the graph to create the clustered layout word cloud. We conducted a two-task user study to compare the clustered layout word cloud to two alternative review reading techniques: random layout word cloud and normal block-text reviews. The results showed that the clustered layout word cloud offers faster task completion time and better user satisfaction level than other two alternative review reading techniques.