TopicWave: Visually Exploring Topics of Hierarchical Time-Oriented Data

• Main Authors: Hsiung, Kai Wen, 熊凱文
• Other Authors: Chi, Ming Te
• Format: Others
• Language: zh-TW
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/mhymj7

碩士 === 國立政治大學 === 資訊科學學系 === 104 === In recent research, it is a frequently asked question about how to explore the topic trend during a time interval. If we want to analysis and discuss this question, time-oriented data will be the most appropriate dataset. For example, on social media platform, major issues are commonly formed by opinion leaders, people will be attracted by opinion leaders and join in the commentary on a topic. The above-mentioned procedure will involve in commentary hierarchy level increasing or decreasing while time changes, however, it is challenging when we want to explore these properties using traditional visualization techniques. We propose TopicWave, a visualization design that combines ThemeRiver Graph (time-oriented visualization) and Sunburst (hierarchical data visualization). It can visualize the trend of a post’s comment on Facebook Page. TopicWave can clearly present hierarchy and time-varying trend of a Facebook post’s comment data at the same time through the intuitive design of interactive on visualization.