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

[1]  Joon-Oh Park,et al.  The Increasing Dominance of Teams in Production of Knowledge , 2011 .

[2]  G. Melin.  Pragmatism and self-organization: Research collaboration on the individual level , 2000 .

[3]  A-L Barabási,et al.  Structure and tie strengths in mobile communication networks , 2006, Proceedings of the National Academy of Sciences.

[4]  Qing Ke,et al.  Tie Strength Distribution in Scientific Collaboration Networks , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

[5]  Jari Saramäki,et al.  The strength of strong ties in scientific collaboration networks , 2011, ArXiv.

[6]  Enrique Orduña-Malea,et al.  Empirical Evidences in Citation-Based Search Engines: Is Microsoft Academic Search dead? , 2014, Online Inf. Rev..

[7]  Timothy L. O’Brien.  Change in Academic Coauthorship, 1953–2003 , 2012 .

[8]  Christian Bauckhage,et al.  Network growth and the spectral evolution model , 2010, CIKM.

[9]  J. Sylvan Katz,et al.  Geographical proximity and scientific collaboration , 1994, Scientometrics.

[10]  Y. Gingras,et al.  The Effects of Aging on Researchers' Publication and Citation Patterns , 2008, PloS one.

[11]  Mark S. Granovetter.  The Strength of Weak Ties , 1973, American Journal of Sociology.

[12]  Loet Leydesdorff,et al.  Network Structure, Self-Organization and the Growth of International Collaboration in Science.Research Policy, 34(10), 2005, 1608-1618. , 2005, 0911.4299.

[13]  J. Ioannidis,et al.  Estimates of the Continuously Publishing Core in the Scientific Workforce , 2014, PloS one.

[14]  Harry Eugene Stanley,et al.  Persistence and uncertainty in the academic career , 2012, Proceedings of the National Academy of Sciences.

[15]  M. Newman,et al.  The structure of scientific collaboration networks. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[16]  M. Newman,et al.  Finding community structure in very large networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[17]  J. S. Katz,et al.  What is research collaboration , 1997 .

[18]  Deokjae Lee,et al.  Complete trails of coauthorship network evolution. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[19]  Kim J. R. Rasmussen,et al.  Network Effects on Scientific Collaborations , 2013, PloS one.

[20]  C. Lee Giles,et al.  Collaboration over time: characterizing and modeling network evolution , 2008, WSDM '08.

[21]  Barry Bozeman,et al.  The Impact of Research Collaboration on Scientific Productivity , 2005 .

[22]  J. Glenn Brookshear.  Computer Science: An Overview , 1985 .