Text Mining Analytics as a Method of Benchmarking Interdisciplinary Research Collaboration

Schröder, Stefan; Thiele, Thomas; Jooß, Claudia; Vossen, René; Richert, Anja; Isenhardt, Ingrid; Jeschke, Sabina

doi:10.1007/978-3-319-42620-4_73

Cited by 3 publications

(3 citation statements)

References 18 publications

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“…Many previous studies have used this database over the past decades (Ramy et al, 2018;Flamini et al, 2022;Maseda et al, 2022). It should be noted that recent studies such as Mohammadi and Karami (2020) and Schröder et al (2015) have adopted a new approach, text mining, to investigate the scope and structure of big data across disciplines. Schröder et al (2015) noted that text mining or clustering algorithms could be used as a benchmark for research clusters.…”

Section: Co-word Analysismentioning

confidence: 99%

“…It should be noted that recent studies such as Mohammadi and Karami (2020) and Schröder et al (2015) have adopted a new approach, text mining, to investigate the scope and structure of big data across disciplines. Schröder et al (2015) noted that text mining or clustering algorithms could be used as a benchmark for research clusters. Future research should incorporate this new approach in the study of TH.…”

Section: Co-word Analysismentioning

confidence: 99%

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Mapping the helix model of innovation influence on education: A bibliometric review

et al. 2023

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As a direct result of the increased significance of knowledge in the various endeavours attempting to implement the triple helix model, higher education institutions have assumed a more prominent position in the processes involved in regional innovation and development. Expanding study on the helix model is currently examining the underlying causes and consequences of the evolution of the helix model in education. This research examines the relationship between the triple helix model and education by using bibliometric analysis on 227 articles subjected to peer review between 1970 and 2022. This investigation concentrated on three aspects of analysis: (1) document citation via the use of co-citation analysis that produce 4 clusters; (2) document cited reference through the utilisation of bibliographic coupling that generates 5 clusters; and (3) document keyword through the utilisation of co-word analysis with 4 clusters. These results are essential for academics, practitioners, and other interested parties working to improve the helix model for policymakers by putting it into an education strategy.

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Section: Co-word Analysismentioning

confidence: 99%

Section: Co-word Analysismentioning

confidence: 99%

Mapping the helix model of innovation influence on education: A bibliometric review

et al. 2023

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“…It is also complemented by a benchmarking section [22] [23]. The first part of this study is concerned with the identification and acquisition of relevant publications.…”

Section: Publicationsmentioning

confidence: 99%

Benchmarking of Scientific Research Clusters by Use of Text Mining Algorithms on Textual Artefacts

Schroeder

Tummel

Isenhardt

et al. 2016

2016 International Conference on Information Systems Engineering (ICISE)

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The development of text mining algorithms is far reaching and thus, new application areas arise, inter alia in the framework of applying modern information technologies (e.g. big data analytics) in order to answer social and economic (research) questions (digital humanities). In this paper existing algorithms to reveal results in the context of benchmarking scientific research clusters are combined. For conducting the analysis, two data corpora are gathered. The first data corpus contains abstracts of publications according to the used application case of the Cluster of Excellence Tailor-Made Fuels from Biomass 'TMFB' at RWTH Aachen University. The second data corpus -based on the analysis of the first data corpus -contains content-related abstracts of research belonging to the relevant scientific community. In the framework of processing the gathered data, information extraction, information retrieval and named entity recognition among others are utilized for analyzing the publications in order to derive useful findings. Furthermore association mining findings are introduced. As an excerpt of the results, the identification of thematic alignments and developments over time are presented for both corpora and are subsequently compared.

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