Research collaboration and topic trends in Computer Science based on top active authors
Academic publication metadata can be used to analyze the collaboration, productivity and hot topic trends of a research community. In this paper, we study a specific group of authors, namely the top active authors. They are defined as the top 1% authors with uninterrupted and continuous presence in scientific publications over a time window. We take the top active authors in the Computer Science (CS) community over different time windows in the past 50 years, and use them to analyze collaboration, productivity and topic trends. We show that (a) the top active authors are representative of the overall population; (b) the community is increasingly moving in the direction of Team Research, with increased level and degree of collaboration; and (c) the research topics are increasingly inter related. By focusing on the top active authors, it helps visualize these trends better. Besides, the observations from top active authors also shed light on design of better evaluation framework and resource management for policy makers in academia. Subjects Data Mining and Machine Learning, Data Science, Digital Libraries, Network Science and Online Social Networks, Social Computing
PeerJ Comput. Sci.