Mapping the evolution of scientific fields has drawn much attention in recent years. Researchers have proposed various methods to describe, explain and predict different aspects of science. Network-based analysis has been widely used for knowledge networks, in order to track the changes of research topics and the spread of scientific ideas. Here we propose a novel approach for mapping the science from the perspective of cross-field authors. Computer science is selected based on its interdisciplinary applications. We build a scientific network consisting of computer science conferences as nodes, and two conferences are linked if there exist authors that published papers on both conferences. The scientific fields are identified by community detection algorithm. The results suggest the proposed method based on author overlaps across fields are effective in mapping the science.
['Xiaoling Sun', 'Kun Ding', 'Yuan Lin']
Mapping the evolution of scientific fields based on cross-field authors