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Is Performance of Scholars Correlated to Their Research Collaboration Patterns?open access

Authors
Jeon, H.-J.Lee, O.-J.Jung, Jason J.
Issue Date
Nov-2019
Publisher
Frontiers Media S.A.
Keywords
bibliographic network embedding; collaboration pattern discovery; research collaboration; research group analysis; research performance estimation
Citation
Frontiers in Big Data, v.2
Journal Title
Frontiers in Big Data
Volume
2
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/53100
DOI
10.3389/fdata.2019.00039
ISSN
2624-909X
2624-909X
Abstract
This study aims to validate whether the research performance of scholars correlates with how the scholars work together. Although the most straightforward approaches are centrality measurements or community detection, scholars mostly participate in multiple research groups and have different roles in each group. Thus, we concentrate on the subgraphs of co-authorship networks rooted in each scholar that cover (i) overlapping of the research groups on the scholar and (ii) roles of the scholar in the groups. This study calls the subgraphs “collaboration patterns” and applies subgraph embedding methods to discover and represent the collaboration patterns. Based on embedding the collaboration patterns, we have clustered scholars according to their collaboration styles. Then, we have examined whether scholars in each cluster have similar research performance, using the quantitative indicators. The coherence of the indicators cannot be solid proofs for validating the correlation between collaboration and performance. Nevertheless, the examination for clusters has exhibited that the collaboration patterns can reflect research styles of scholars. This information will enable us to predict the research performance more accurately since the research styles are more consistent and sustainable features of scholars than a few high-impact publications. Copyright © 2019 Jeon, Lee and Jung.
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Jung, Jason J.
소프트웨어대학 (소프트웨어학부)
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