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ScholarSight: Visualizing Temporal Trends of Scientific Concepts

Färber, Michael ORCID iD icon 1; Nishioka, Chifumi; Jatowt, Adam
1 Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB), Karlsruher Institut für Technologie (KIT)

Abstract:

In this paper, we present a system for exploring the temporal trends of scientific concepts. Scientific concepts were captured by extracting noun phrases and entities from all computer science papers of arXiv.org. Our system allows users to review the time series of numerous concepts and to identify positively and negatively trending concepts. By applying clustering techniques and cluster analysis visualizations, it can also present concepts which share the same usage patterns over time. Our system can be beneficial for both ordinary researchers of any field and for researchers working in bibliometrics and scientometrics in order to investigate the evolution of scientific concepts.


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Originalveröffentlichung
DOI: 10.1109/JCDL.2019.00108
Scopus
Zitationen: 7
Zugehörige Institution(en) am KIT Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB)
Publikationstyp Proceedingsbeitrag
Publikationsmonat/-jahr 06.2019
Sprache Englisch
Identifikator ISBN: 978-1-7281-1548-1
KITopen-ID: 1000175818
Erschienen in 2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL), Champaign, IL, USA, 02-06 June 2019
Veranstaltung ACM/IEEE Joint Confernce on Digital Libraries (JCDL 2019), Champaign, IL, USA, 02.06.2019 – 06.06.2019
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Seiten 438–439
Nachgewiesen in Scopus
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