Same same, but different ? On the Relation of Information Science and the Digital Humanities A Scientometric Comparison of Academic Journals Using LDA and Hierarchical Clustering

URN to cite this document:

urn:nbn:de:bvb:355-epub-449447 Copy

DOI to cite this document:

10.5283/epub.44944 Copy

Burghardt, Manuel ; Luhmann, Jan

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Date of publication of this fulltext: 18 Apr 2021 10:22

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Details

Item type:	Book section
ISBN:	978-3-86488-172-5
Open Access Type:	Individuel Contract
Title of Book:	Information between Data and Knowledge
Publisher:	Werner Hülsbusch
Place of Publication:	Glückstadt
Other Series:	Schriften zur Informationswissenschaft
Volume:	74
Page Range:	pp. 173-199
Date:	2021
Additional Information (public):	Session 3: Digital Humanities
Institutions:	Languages and Literatures > Institut für Information und Medien, Sprache und Kultur (I:IMSK) > Lehrstuhl für Medieninformatik (Prof. Dr. Christian Wolff) Informatics and Data Science > Department Human-Centered Computing > Lehrstuhl für Medieninformatik (Prof. Dr. Christian Wolff)
Keywords:	scientometrics; Information Science; Digital Humanities; LDA topic modeling; hierarchical clustering
Dewey Decimal Classification:	000 Computer science, information & general works > 020 Library & information sciences
Status:	Published
Refereed:	Yes, this version has been refereed
Created at the University of Regensburg:	No
Item ID:	44944

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Abstract

In this paper we investigate the relationship of Information Science (IS) and the Digital Humanities (DH) by means of a scientometric comparison of academic journals from the respective disciplines. In order to identify scholarly practices for both disciplines, we apply a recent variant of LDA topic modeling that makes use of additional hierarchical clustering. The results reveal the existence of ...

Abstract

In this paper we investigate the relationship of Information Science (IS) and the Digital Humanities (DH) by means of a scientometric comparison of academic journals from the respective disciplines. In order to identify scholarly practices for both disciplines, we apply a recent variant of LDA topic modeling that makes use of additional hierarchical clustering. The results reveal the existence of characteristic topic areas for both IS (information retrieval, information seeking behavior, scientometrics) and DH (computational linguistics, distant reading and digital editions) that can be used to distinguish them as disciplines in their own right. However, there is also a larger shared area of practices related to information management and also a few shared topic clusters that indicate a common ground for – mostly methodological – exchange between the two disciplines.

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Metadata last modified: 18 Apr 2021 10:22

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