VR system for spatio-temporal visualization of tweet data and support of map exploration

Social media analysis is helpful to understand the behavior of people. Human behavior in social media is related to time and location, which is often difficult to find the characteristics appropriately and quickly. We chose to apply virtual reality (VR) technologies to present the spatio-temporal social media data. This makes us easier to develop interactive and intuitive user interfaces and explore the data as we want. This paper proposes a VR system featuring two visualization techniques. One of the techniques is a three-dimensional temporal visualization of tweets of microblogs with location information. It consists of the two-dimensional map and a time axis. In particular, we aggregate the number of tweets of each coordinate and time step and depict them as piled cubes. We highlight only specific cubes so that users can understand the overall tendency of datasets. The other technique provides a route recommendation based on tweets of microblogs. Our technique supports users to explore attractive events and places by selecting effective tweets and suggesting routes. We also developed user interfaces for operating these objects in a VR space which indicate details of tweets.