Code for: Mining Twitter to Detect Hotspots in Psychology
Author(s) / Creator(s)
Bittermann, André
Batzdorfer, Veronika
Müller, Sarah Marie
Steinmetz, Holger
Abstract / Description
Code for: Bittermann, A., Batzdorfer, V., Müller, S. M., & Steinmetz, H. (2021). Mining Twitter to detect hotspots in psychology. Zeitschrift für Psychologie, 229(1), 3–14. https://doi.org/10.1027/2151-2604/a000437
For identifying psychological hotspot topics, a mere focus on bibliometric data suffers from a publication delay. To overcome this issue, we introduce Twitter mining of ongoing online communication among scientists for the detection of psychological research topics. Specifically, we collected the entire 69,963 tweets posted between August 2007 and July 2020 from 139 accounts of psychology professors, departments, and research institutes from the German-speaking countries, as well as sections of the German Psychological Society (DGPs). To examine whether Twitter topics are hotspots in terms of indicating future publication trends, 346,361 references in the PSYNDEX database were extracted. For determining the additional value of our approach in contrast to traditional conference analysis, we gathered all available conference programs of the DGPs and its sections since 2010 and compared dates of topic emergence. Results revealed 21 topics addressing societal issues (e.g., COVID-19), methodology (e.g., machine learning), scientific research (e.g., replication crisis), and different areas of psychological research. Ten topics indicated an increasing publication trend, particularly topics related to methodology or scientific transparency. Seven Twitter topics emerged earlier on Twitter than at conferences. A total of four topics could be expected neither by bibliometric forecasting nor conference contents: “methodological issues in meta-analyses”, “playfulness”, “preregistration”, and “mobile brain/body imaging”. Taken together, Twitter mining is a worthwhile endeavor for identifying psychological hotspot topics, especially regarding societal issues, novel research methods, and research transparency in psychology. In order to get the most comprehensive picture of research hotspots, Twitter mining is recommended in addition to bibliometric analyses of publication trends and monitoring of conference topics.
Keyword(s)
Twitter hot topics research topics biterm topic model publication trendsPersistent Identifier
Date of first publication
2020-11-30
Publisher
PsychArchives
Is referenced by
Citation
Bittermann, A., Batzdorfer, V., Müller, S. M., & Steinmetz, H. (2020). Code for: Mining Twitter to Detect Hotspots in Psychology. PsychArchives. https://doi.org/10.23668/PSYCHARCHIVES.4372
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ESM 2_R_code.zipUnknown - 21.5KBMD5: 5b8d420c603e172c78fbb95f24779de4Description: ESM 2 - R Code
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There are no other versions of this object.
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Author(s) / Creator(s)Bittermann, André
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Author(s) / Creator(s)Batzdorfer, Veronika
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Author(s) / Creator(s)Müller, Sarah Marie
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Author(s) / Creator(s)Steinmetz, Holger
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PsychArchives acquisition timestamp2020-11-30T09:08:30Z
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Made available on2020-11-30T09:08:30Z
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Date of first publication2020-11-30
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Abstract / DescriptionCode for: Bittermann, A., Batzdorfer, V., Müller, S. M., & Steinmetz, H. (2021). Mining Twitter to detect hotspots in psychology. Zeitschrift für Psychologie, 229(1), 3–14. https://doi.org/10.1027/2151-2604/a000437en
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Abstract / DescriptionFor identifying psychological hotspot topics, a mere focus on bibliometric data suffers from a publication delay. To overcome this issue, we introduce Twitter mining of ongoing online communication among scientists for the detection of psychological research topics. Specifically, we collected the entire 69,963 tweets posted between August 2007 and July 2020 from 139 accounts of psychology professors, departments, and research institutes from the German-speaking countries, as well as sections of the German Psychological Society (DGPs). To examine whether Twitter topics are hotspots in terms of indicating future publication trends, 346,361 references in the PSYNDEX database were extracted. For determining the additional value of our approach in contrast to traditional conference analysis, we gathered all available conference programs of the DGPs and its sections since 2010 and compared dates of topic emergence. Results revealed 21 topics addressing societal issues (e.g., COVID-19), methodology (e.g., machine learning), scientific research (e.g., replication crisis), and different areas of psychological research. Ten topics indicated an increasing publication trend, particularly topics related to methodology or scientific transparency. Seven Twitter topics emerged earlier on Twitter than at conferences. A total of four topics could be expected neither by bibliometric forecasting nor conference contents: “methodological issues in meta-analyses”, “playfulness”, “preregistration”, and “mobile brain/body imaging”. Taken together, Twitter mining is a worthwhile endeavor for identifying psychological hotspot topics, especially regarding societal issues, novel research methods, and research transparency in psychology. In order to get the most comprehensive picture of research hotspots, Twitter mining is recommended in addition to bibliometric analyses of publication trends and monitoring of conference topics.en
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Publication statusunknownen
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Review statusunknownen
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Table of contentsTwitter_preprocessing.R; Twitter_BTM.R; Twitter_forecasting.R; Twitter_additionalResults.R; Source filesen
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CitationBittermann, A., Batzdorfer, V., Müller, S. M., & Steinmetz, H. (2020). Code for: Mining Twitter to Detect Hotspots in Psychology. PsychArchives. https://doi.org/10.23668/PSYCHARCHIVES.4372en
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Persistent Identifierhttps://hdl.handle.net/20.500.12034/3955
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Persistent Identifierhttps://doi.org/10.23668/psycharchives.4372
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Language of contenteng
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PublisherPsychArchivesen
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Is referenced byhttps://doi.org/10.1027/2151-2604/a000437
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Is related tohttps://doi.org/10.23668/psycharchives.4373
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Is related tohttps://doi.org/10.1027/2151-2604/a000437
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Keyword(s)Twitteren
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Keyword(s)hot topicsen
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Keyword(s)research topicsen
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Keyword(s)biterm topic modelen
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Keyword(s)publication trendsen
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Dewey Decimal Classification number(s)150
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TitleCode for: Mining Twitter to Detect Hotspots in Psychologyen
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DRO typecodeen
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Leibniz institute name(s) / abbreviation(s)ZPIDde_DE
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Visible tag(s)Hogrefede_DE