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Positionspapier der DMV zur Verwendung bibliometrischer Daten (2020) 0.04
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Abstract

Bibliometrische Daten werden heute zunehmend in der Evaluation von Forschungsergebnissen benutzt. Diese Anwendungen reichen von der (indirekten) Verwendung bei der Peer-Evaluation von Drittmittelanträgen über die Beurteilung von Bewerbungen in Berufungskommissionen oder Anträgen für Forschungszulagen bis hin zur systematischen Erhebung von forschungsorientierten Kennzahlen von Institutionen. Mit diesem Dokument will die DMV ihren Mitgliedern eine Diskussionsgrundlage zur Verwendung bibliometrischer Daten im Zusammenhang mit der Evaluation von Personen und Institutionen im Fachgebiet Mathematik zur Verfügung stellen, insbesondere auch im Vergleich zu anderen Fächern. Am Ende des Texts befindet sich ein Glossar, in dem die wichtigsten Begriffe kurz erläutert werden.
Tausch, A.: Zitierungen sind nicht alles : Classroom Citation, Libcitation und die Zukunft bibliometrischer und szientometrischer Leistungsvergleiche (2022) 0.02
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Abstract

Der Beitrag soll zeigen, welche fortgeschrittenen bibliometrischen und szientometrischen Daten für ein bewährtes Sample von 104 österreichischen Politikwissenschaftler*innen und 51 transnationalen Verlagsunternehmen enge statistische Beziehungen zwischen Indikatoren der Präsenz von Wissenschaftler*innen und transnationalen Verlagsunternehmen in den akademischen Lehrveranstaltungen der Welt (Classroom Citation, gemessen mit Open Syllabus) und anderen, herkömmlicheren bibliometrischen und szientometrischen Indikatoren (Libcitation gemessen mit dem OCLC Worldcat, sowie der H-Index der Zitierung in den vom System Scopus erfassten Fachzeitschriften der Welt bzw. dem Book Citation Index) bestehen. Die statistischen Berechnungen zeigen, basierend auf den Faktorenanalysen, die engen statistischen Beziehungen zwischen diesen Dimensionen. Diese Ergebnisse sind insbesondere in den Tabellen 5 und 9 dieser Arbeit (Komponentenkorrelationen) ableitbar.

Manley, S.: Letters to the editor and the race for publication metrics (2022) 0.01

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Date: 6. 4.2022 19:22:26

Lorentzen, D.G.: Bridging polarised Twitter discussions : the interactions of the users in the middle (2021) 0.01

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Date: 20. 1.2015 18:30:22

Milard, B.; Pitarch, Y.: Egocentric cocitation networks and scientific papers destinies (2023) 0.01

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Date: 21. 3.2023 19:22:14

Thelwall, M.; Thelwall, S.: ¬A thematic analysis of highly retweeted early COVID-19 tweets : consensus, information, dissent and lockdown life (2020) 0.01

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Date: 20. 1.2015 18:30:22

Wang, S.; Ma, Y.; Mao, J.; Bai, Y.; Liang, Z.; Li, G.: Quantifying scientific breakthroughs by a novel disruption indicator based on knowledge entities : On the rise of scrape-and-report scholarship in online reviews research (2023) 0.01

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Date: 22. 1.2023 18:37:33

Cerda-Cosme, R.; Méndez, E.: Analysis of shared research data in Spanish scientific papers about COVID-19 : a first approach (2023) 0.01

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Date: 21. 3.2023 19:22:02

Asubiaro, T.V.; Onaolapo, S.: ¬A comparative study of the coverage of African journals in Web of Science, Scopus, and CrossRef (2023) 0.01

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Date: 22. 6.2023 14:09:06

Zhang, Y.; Wu, M.; Zhang, G.; Lu, J.: Stepping beyond your comfort zone : diffusion-based network analytics for knowledge trajectory recommendation (2023) 0.01

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Date: 22. 6.2023 18:07:12

Thelwall, M.; Kousha, K.; Abdoli, M.; Stuart, E.; Makita, M.; Wilson, P.; Levitt, J.: Why are coauthored academic articles more cited : higher quality or larger audience? (2023) 0.01

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Date: 22. 6.2023 18:11:50

Vakkari, P.; Järvelin, K.; Chang, Y.-W.: ¬The association of disciplinary background with the evolution of topics and methods in Library and Information Science research 1995-2015 (2023) 0.01

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Date: 22. 6.2023 18:15:06

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