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Title
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Measurement of interdisciplinarity : quantifying distance‐based disparity using Node2vec
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Author
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Abstract
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| When quantifying the level of interdisciplinarity for scientific research, most established indicators employ a three-element diversity framework, namely variety, balance, and disparity, each of which captures a distinct but insufficient element. Among three, disparity, i.e. how different (dissimilar) the categories within a system are, is the most challenging one due to its calculation cost and conceptual ambiguity. The discriminative power for disparity is found to be weakened in more fine-grained science classification schemes. To address this issue, this paper proposes a new method for quantifying disparity by applying Node2vec on the discipline citation network and retrieving distance between disciplines using embeddings vectors. Compared to cosine-based dissimilarity for disparity, our proposed method exhibited broader distribution and less skewness for disparity values, which could potentially lead to higher discriminative power of interdisciplinarity. A case study for Linguistics is also conducted to show the capability of detecting variations in disparity of the proposed method. |
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Language
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English
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Source (journal)
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Proceedings of the Association for Information Science and Technology. - -
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Proceedings of the Association for Information Science and Technology
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Source (book)
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84th Annual Meeting of the Association for Information Science & Technology, October 29 – November 3, 2021, Salt Lake City, Utah, USA
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Publication
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Wiley
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2021
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ISSN
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2373-9231
[online]
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DOI
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10.1002/PRA2.498
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Volume/pages
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58
:1
(2021)
, p. 563-566
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Full text (Publisher's DOI)
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Full text (publisher's version - intranet only)
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