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Analysis of University Researcher Collaboration Networks using co-authorship

Analysis of University Researcher Collaboration Networks using co-authorship
Analysis of University Researcher Collaboration Networks using co-authorship
Social network analysis gives evidence for the connections between groups of individuals. It is these connections that channel flow of information and the sharing of knowledge. As universities move towards more interdisciplinary modes of research and funding, an effective network that links its entire cohort of active researchers is vital. This project conducted a co-authorship network analysis and a path length analysis on a small institutional database. The major advantage of our analysis over other similar work is that we used author's background details in supporting our analysis and generated co-authorship graphs with authors' names and groups. The network metrics have been compared and contrasted to similar work conducted with large-scale cross-institutional databases in several domains. We found the most of metrics are not affected by the network size and showed that the ECS community is a small-world network with similar knowledge sharing to those communities formed by an entire discipline.
Yao, Jiadi
b9c01cc2-b141-4656-86a9-22cd1c793fa9
Yao, Jiadi
b9c01cc2-b141-4656-86a9-22cd1c793fa9

Yao, Jiadi (2009) Analysis of University Researcher Collaboration Networks using co-authorship. University of Southampton, School of Electronic and Computer Science, Masters Thesis.

Record type: Thesis (Masters)

Abstract

Social network analysis gives evidence for the connections between groups of individuals. It is these connections that channel flow of information and the sharing of knowledge. As universities move towards more interdisciplinary modes of research and funding, an effective network that links its entire cohort of active researchers is vital. This project conducted a co-authorship network analysis and a path length analysis on a small institutional database. The major advantage of our analysis over other similar work is that we used author's background details in supporting our analysis and generated co-authorship graphs with authors' names and groups. The network metrics have been compared and contrasted to similar work conducted with large-scale cross-institutional databases in several domains. We found the most of metrics are not affected by the network size and showed that the ECS community is a small-world network with similar knowledge sharing to those communities formed by an entire discipline.

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MSc_DissertationResearcher-collaboration.pdf - Author's Original
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More information

Submitted date: 25 September 2009
Organisations: University of Southampton, Electronics & Computer Science

Identifiers

Local EPrints ID: 268175
URI: https://eprints.soton.ac.uk/id/eprint/268175
PURE UUID: a53c60cd-60bc-4f40-b939-8e290d7ed0ae

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Date deposited: 03 Nov 2009 17:44
Last modified: 06 Mar 2019 17:32

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