Authors: Zeyu Li, Changhong Zhang, Shichao Jia, Jiawan Zhang
Abstract: Revealing the evolution of science and intersections among its sub-fields is extremely important for understanding the characteristics of discipline, discovering new topics, and even predicting the future. The current works either focus on building a skeleton of science, lacking interaction, detail exploration and interpretation, or on the lower topic level, missing the high-level macro perspective. To fill this gap, we design and implement Galex, a hierarchical visual analysis system, combining with advanced text mining technologies, could help analysts to comprehend the evolution and intersection of one discipline rapidly. We divide Galex into the following three progressively fine-grained levels: discipline level, area level and institution level. The cooperations between interactions enable analysts to explore an arbitrary piece of history and an arbitrary part of the knowledge space of one discipline. Using a flexible spotlight component, analysts could freely choose and quickly understand an exploration region. A tree metaphor allows perceiving the expansion, decline and intersection of topics intuitively. A synchronous spotlight interaction helps to compare research content among institutions easily. Three case studies and expert reviews demonstrate the effectiveness of our system.
