The Merits of Screening Automation for Bibliometric Analyses: The Case of Translational Psychotherapy
Author(s) / Creator(s)
Petrule, Claudiu
Bittermann, André
Ritter, Viktoria
Haberkamp, Anke
Rief, Winfried
Abstract / Description
Analyzing emerging fields using traditional bibliometric techniques can be difficult due to inconsistent terminology and vague or porous boundaries. The absence of precise terms for database search queries can hinder efforts to fully cover a given construct of interest and may result in biased or distorted representations. The common solution of widening the scope of the search can lead to the inclusion of a large number of false positives, making it difficult to distinguish eligible data from noise. As a consequence, the drastically increased amount of records makes screening an absolute requirement for building a complete and accurate dataset.
Keyword(s)
machine learning metascience methods and techniques screening automation translational researchPersistent Identifier
Date of first publication
2023-07-03
Is part of
Big Data & Research Syntheses 2023, Frankfurt, Germany
Publisher
ZPID (Leibniz Institute for Psychology)
Citation
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Ressyn Big-Data_ The Merits of Screening Automation for Bibliometric Analyses_ The Case of Translational Psychotherapy.pdfAdobe PDF - 3.38MBMD5: 54070398139dacf38a2cbac87c3f1b1aDescription: Conference Presentation
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32023-07-03Updated the authors on metadata level to reflect the entire team involved in the project, not only the presenter. Updated the copyright level to CC BY 4.0.
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22023-05-16Updated the authors on the first page to reflect the entire team involved in the project, not only the presenter.
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Author(s) / Creator(s)Petrule, Claudiu
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Author(s) / Creator(s)Bittermann, André
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Author(s) / Creator(s)Ritter, Viktoria
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Author(s) / Creator(s)Haberkamp, Anke
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Author(s) / Creator(s)Rief, Winfried
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PsychArchives acquisition timestamp2023-07-03T14:12:23Z
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Made available on2023-05-03T12:59:52Z
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Made available on2023-05-16T14:45:52Z
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Made available on2023-07-03T14:12:23Z
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Date of first publication2023-07-03
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Abstract / DescriptionAnalyzing emerging fields using traditional bibliometric techniques can be difficult due to inconsistent terminology and vague or porous boundaries. The absence of precise terms for database search queries can hinder efforts to fully cover a given construct of interest and may result in biased or distorted representations. The common solution of widening the scope of the search can lead to the inclusion of a large number of false positives, making it difficult to distinguish eligible data from noise. As a consequence, the drastically increased amount of records makes screening an absolute requirement for building a complete and accurate dataset.en_US
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Publication statusunknownen
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Review statusunknownen
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Persistent Identifierhttps://hdl.handle.net/20.500.12034/8365.3
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Persistent Identifierhttps://doi.org/10.23668/psycharchives.12961
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Language of contentengen_US
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PublisherZPID (Leibniz Institute for Psychology)en_US
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Is part ofBig Data & Research Syntheses 2023, Frankfurt, Germanyen_US
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Is related tohttps://doi.org/10.23668/psycharchives.13006
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Is related tohttps://doi.org/10.23668/psycharchives.15204
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Keyword(s)machine learningen_US
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Keyword(s)metascienceen_US
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Keyword(s)methods and techniquesen_US
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Keyword(s)screening automationen_US
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Keyword(s)translational researchen_US
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Dewey Decimal Classification number(s)150
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TitleThe Merits of Screening Automation for Bibliometric Analyses: The Case of Translational Psychotherapyen_US
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DRO typeconferenceObjecten_US
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Leibniz institute name(s) / abbreviation(s)ZPIDde_DE
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Visible tag(s)ZPID Conferences and Workshops