Analysis of intra-institutional research collaboration: a case of a Serbian faculty of sciences

Current research information systems (CRISs) offer great opportunities for scientometric studies of institutional research outputs. However, many of these opportunities have not been explored in depth, especially for the analysis of intra-institutional research collaboration. In this paper, we propose a hybrid methodology to analyze research collaboration networks with an underlying institutional structure. The co-authorship network extracted from the institutional CRIS of the Faculty of Sciences, University of Novi Sad, Serbia, is analyzed using the proposed methodology. The obtained results show that the organizational structure of the institution has a profound impact on both inter- and intra-institutional research collaboration. Moreover, researchers involved in inter-department collaborations tend to be drastically more productive (by all considered productivity measures), collaborative (measured by the number of co-authorship relations) and institutionally important (in terms of the betweenness centrality in the co-authorship network) compared to those who collaborate only with colleagues from their own research departments. Finally, our results indicate that quantifying research productivity by the normal counting scheme and Serbian research competency index is biased towards researchers from physics and chemistry research departments.

[1]  M. Newman,et al.  Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[2]  Jure Leskovec,et al.  Empirical comparison of algorithms for network community detection , 2010, WWW '10.

[3]  Shilpa Chakravartula,et al.  Complex Networks: Structure and Dynamics , 2014 .

[4]  Dragan Ivanovic,et al.  A CERIF data model extension for evaluation and quantitative expression of scientific research results , 2010, Scientometrics.

[5]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[6]  M. Newman.  Coauthorship networks and patterns of scientific collaboration , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[7]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[8]  Duncan Lindsey,et al.  Production and Citation Measures in the Sociology of Science: The Problem of Multiple Authorship , 1980 .

[9]  Dragan Ivanovic,et al.  A CERIF-compatible research management system based on the MARC 21 format , 2010, Program.

[10]  Santo Fortunato,et al.  Community detection in graphs , 2009, ArXiv.

[11]  D. Lindsey.  The Problem of Multiple Authorship , 2016 .

[12]  Giuseppe Giordano,et al.  Issues in the analysis of co-authorship networks , 2011 .

[13]  Vladimir Batagelj,et al.  On bibliographic networks , 2013, Scientometrics.

[14]  Luís M. A. Bettencourt,et al.  Scientific discovery and topological transitions in collaboration networks , 2009, J. Informetrics.

[15]  W. Kruskal,et al.  Use of Ranks in One-Criterion Variance Analysis , 1952 .

[16]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[17]  Zoran Ognjanovic,et al.  Exploratory Analysis of Communities in Co-authorship Networks: A Case Study , 2014, ICT Innovations.

[18]  David M Erceg-Hurn,et al.  Modern robust statistical methods: an easy way to maximize the accuracy and power of your research. , 2008, The American psychologist.

[19]  W. Glänzel,et al.  Analysing Scientific Networks Through Co-Authorship , 2004 .

[20]  Claudio Castellano,et al.  Defining and identifying communities in networks. , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[21]  Leonard M. Freeman,et al.  A set of measures of centrality based upon betweenness , 1977 .

[22]  Dragan Ivanovic,et al.  Journal evaluation based on bibliometric indicators and the CERIF data model , 2012, Comput. Sci. Inf. Syst..

[23]  Miloš Savić.  Extraction and analysis of complex networks from different domains , 2015 .

[24]  M E J Newman.  Assortative mixing in networks. , 2002, Physical review letters.

[25]  Henk F. Moed,et al.  Handbook of Quantitative Science and Technology Research: The Use of Publication and Patent Statistics in Studies of S&T Systems , 2004 .

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

[27]  L. Bellanca.  Measuring interdisciplinary research: analysis of co-authorship for research staff at the University of York , 2009 .

[28]  Attila Kiss,et al.  Betweenness versus Linerank , 2014, Comput. Sci. Inf. Syst..

[29]  Sameer Kumar,et al.  Co-authorship networks: a review of the literature , 2015, Aslib J. Inf. Manag..

[30]  M. Newman.  1 Who is the best connected scientist ? A study of scientific coauthorship networks , 2004 .

[31]  Shion Guha,et al.  Cross-campus collaboration: A scientometric and network case study of publication activity across two campuses of a single institution , 2013, J. Assoc. Inf. Sci. Technol..

[32]  Jure Leskovec,et al.  Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters , 2008, Internet Math..

[33]  Paul J. Campbell,et al.  Patterns of Collaboration in Mathematical Research (Book) , 2003 .

[34]  Matjaz Perc,et al.  Growth and structure of Slovenia's scientific collaboration network , 2010, J. Informetrics.

[35]  Thed N. van Leeuwen,et al.  Bibliometric analysis of output and impact based on CRIS data: a case study on the registered output of a Dutch university , 2015, Scientometrics.

[36]  A. Barabasi,et al.  Evolution of the social network of scientific collaborations , 2001, cond-mat/0104162.

[37]  Stasa Milojevic,et al.  Modes of collaboration in modern science: Beyond power laws and preferential attachment , 2010, J. Assoc. Inf. Sci. Technol..

[38]  Xiaodong Li,et al.  Detecting overlapping community in complex network based on node similarity , 2015, Comput. Sci. Inf. Syst..

[39]  Yuqiang Feng,et al.  A measure of authors’ centrality in co-authorship networks based on the distribution of collaborative relationships , 2009, Scientometrics.

[40]  Zoran Ognjanovic,et al.  The structure and evolution of scientific collaboration in Serbian mathematical journals , 2014, Scientometrics.

[41]  魏屹东,et al.  Scientometrics , 2018, Encyclopedia of Big Data.

[42]  M E Newman,et al.  Scientific collaboration networks. I. Network construction and fundamental results. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[43]  P. Harvey.  Issues of analysis , 1986, Nature.

[44]  Marko A. Rodriguez,et al.  Collaboration in sensor network research: an in-depth longitudinal analysis of assortative mixing patterns , 2009, Scientometrics.

[45]  H. B. Mann,et al.  On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other , 1947 .