Assessing researcher interdisciplinarity: a case study of the University of Hawaii NASA Astrobiology Institute

Michael Gowanlock () and Rich Gazan ()
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Michael Gowanlock: University of Hawaii
Rich Gazan: University of Hawaii

Scientometrics, 2013, vol. 94, issue 1, No 8, 133-161

Abstract: Abstract In this study, we combine bibliometric techniques with a machine learning algorithm, the sequential information bottleneck, to assess the interdisciplinarity of research produced by the University of Hawaii NASA Astrobiology Institute (UHNAI). In particular, we cluster abstract data to evaluate Thomson Reuters Web of Knowledge subject categories as descriptive labels for astrobiology documents, assess individual researcher interdisciplinarity, and determine where collaboration opportunities might occur. We find that the majority of the UHNAI team is engaged in interdisciplinary research, and suggest that our method could be applied to additional NASA Astrobiology Institute teams in particular, or other interdisciplinary research teams more broadly, to identify and facilitate collaboration opportunities.

Keywords: Astrobiology; Bibliometrics; Information bottleneck method; Interdisciplinary science; Machine learning; Text mining (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (9)

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DOI: 10.1007/s11192-012-0765-y

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