Title :
Using Field of Research Codes to Discover Research Groups from Co-authorship Networks
Author :
Qinxue Meng ; Kennedy, Paul J.
Author_Institution :
Centre for Quantum Comput. & Intell. Syst., Univ. of Technol., Sydney, Sydney, NSW, Australia
Abstract :
Nowadays, academic collaboration has become more prevalent and crucial than ever before and many studies of academic collaboration analysis are implemented based on coauthor ship networks. This paper aims to build a novel coauthor ship network by importing field of research codes based on Newman´s model, and then analyze and extract research groups via spectral clustering. In order to explain the effectiveness of this revised network, we take the academic collaboration at the University of Technology, Sydney (UTS) as an example. The result of this study advances methods for selecting the most prolific research groups and individuals in research institutions, and provides scientific evidence for policymakers to manage laboratories and research groups more efficiently in the future.
Keywords :
data mining; educational computing; groupware; pattern clustering; Newman model; academic collaboration; coauthor ship network; coauthorship network; laboratory management; research code; research group discovery; research institution; scientific evidence; spectral clustering; Australia; Collaboration; Communities; Educational institutions; Eigenvalues and eigenfunctions; Laboratories; Social network services; academic collaboration; academic network; academic networks; coauthorship; spectral clustering;
Conference_Titel :
Advances in Social Networks Analysis and Mining (ASONAM), 2012 IEEE/ACM International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4673-2497-7
DOI :
10.1109/ASONAM.2012.56
