Is Performance of Scholars Correlated to Their Research Collaboration Patterns?
DC Field | Value | Language |
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dc.contributor.author | Jeon, H.-J. | - |
dc.contributor.author | Lee, O.-J. | - |
dc.contributor.author | Jung, Jason J. | - |
dc.date.accessioned | 2022-01-10T04:40:26Z | - |
dc.date.available | 2022-01-10T04:40:26Z | - |
dc.date.issued | 2019-11 | - |
dc.identifier.issn | 2624-909X | - |
dc.identifier.issn | 2624-909X | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/53100 | - |
dc.description.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. | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Frontiers Media S.A. | - |
dc.title | Is Performance of Scholars Correlated to Their Research Collaboration Patterns? | - |
dc.type | Article | - |
dc.identifier.doi | 10.3389/fdata.2019.00039 | - |
dc.identifier.bibliographicCitation | Frontiers in Big Data, v.2 | - |
dc.description.isOpenAccess | Y | - |
dc.identifier.wosid | 000682708600001 | - |
dc.identifier.scopusid | 2-s2.0-85099878529 | - |
dc.citation.title | Frontiers in Big Data | - |
dc.citation.volume | 2 | - |
dc.type.docType | Article | - |
dc.publisher.location | 스위스 | - |
dc.subject.keywordAuthor | bibliographic network embedding | - |
dc.subject.keywordAuthor | collaboration pattern discovery | - |
dc.subject.keywordAuthor | research collaboration | - |
dc.subject.keywordAuthor | research group analysis | - |
dc.subject.keywordAuthor | research performance estimation | - |
dc.subject.keywordPlus | SCIENTIFIC IMPACT | - |
dc.subject.keywordPlus | CO-AUTHORSHIP | - |
dc.subject.keywordPlus | INDEX | - |
dc.subject.keywordPlus | GRAPH | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Science & Technology - Other Topics | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
dc.relation.journalWebOfScienceCategory | Multidisciplinary Sciences | - |
dc.description.journalRegisteredClass | scopus | - |
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