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Measuring the extent of interdisciplinary research and creating a collaboration group structure at KTH
KTH, School of Computer Science and Communication (CSC).
KTH, School of Computer Science and Communication (CSC).
2016 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

With interdisciplinary research being a possibility in modern research environ- ments, it is interesting to optimise collaborations between researchers in order to further develop the research environment. The scope of this thesis was therefore to develop a method to measure how widespread the interdisciplinary research is and to propose collaboration groups of researchers created by the use of graph theory.

This problem was approached by studying the research at KTH by col- lecting research publications from the publication database DiVA using a web crawler. Then representing the authors of the publications as nodes and the collaborations between two authors as edges in a graph. A graph partitioning algorithm developed by Flake et al. was chosen after a literature study, then applied to the graph to produce the requested collaboration groups.

The results showed that while interdisciplinary research is not the norm at KTH, 23% of the proposed collaboration groups consisted of two or more researchers from different schools at KTH. The original ratio of school associ- ation was retained through the partitioning of the graph. A measurement of collaboration per researcher in each collaboration group was suggested and the calculated values of these measurements was found to be largely in the same range, with the exception of one collaboration group. The results also high- lighted some inconsistencies in DiVA.

The conclusions were that interdisciplinary research was not very widespread at KTH, however 77 groups were suggested which could be of use for researchers at KTH from now on and in the future. A conclusion was also that this method for finding suitable collaboration groups could be applied at other universities where perhaps interdisciplinary research is more frequent. 

Place, publisher, year, edition, pages
National Category
Computer Science
URN: urn:nbn:se:kth:diva-186442OAI: diva2:927320
Available from: 2016-05-18 Created: 2016-05-11 Last updated: 2016-05-18Bibliographically approved

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