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Date

22. 7.2006 15:22:28

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Abstract

Gegenüberstellung der Berechnung des h-Index in den drei Tools mit Beispiel Stephen Hawking (WoS: 59, Scopus: 19, Google Scholar: 76)

Object

h-index

Source

https://dspace.ndlr.ie/jspui/bitstream/10633/27353/9/H%20index%20datasheet.pdf

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Abstract

Diese Note legt dar, dass der sogenannte h-Index (Hirschs bibliometrischer Index) im Wesentlichen dieselbe Information wiedergibt wie die Gesamtanzahl von Zitationen von Publikationen einer Autorin oder eines Autors, also ein nutzloser bibliometrischer Index ist. Dies basiert auf einem faszinierenden Satz der Wahrscheinlichkeitstheorie, der hier ebenfalls erläutert wird.

Content

Vgl.: DOI: 10.1515/dmvm-2021-0050. Auch abgedruckt u.d.T.: 'Der h-Index - "ein nutzloser bibliometrischer Index"' in Open Password Nr. 1007 vom 06.12.2021 unter: https://www.password-online.de/?mailpoet_router&endpoint=view_in_browser&action=view&data=WzM3NCwiZDI3MzMzOTEwMzUzIiwwLDAsMzQ4LDFd.

Object

h-index

Source

Mitteilungen der Deutschen Mathematiker-Vereinigung. 2021, H.3, S.124-128

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Abstract

The h-index has been shown to increase in many cases mostly because of citations to rather old publications. This inertia can be circumvented by restricting the evaluation to a citation time window. Here I report results of an empirical study analyzing the evolution of the thus defined timed h-index in dependence on the length of the citation time window.

Object

h-index

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Abstract

Publication in academic journals is a key criterion for appointment, tenure and promotion in universities. Many universities weigh publications according to the quality or impact of the journal. Traditionally, journal quality has been assessed through the ISI Journal Impact Factor (JIF). This paper proposes an alternative metric - Hirsch's h-index - and data source - Google Scholar - to assess journal impact. Using a systematic comparison between the Google Scholar h-index and the ISI JIF for a sample of 838 journals in Economics & Business, we argue that the former provides a more accurate and comprehensive measure of journal impact.

Object

h-index

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Object

h-index

Source

Mitteilungen der Deutschen Mathematiker-Vereinigung. 2019, H.3-4, S.112-117

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Object

h-Index

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Abstract

If you are an academic researcher but did not earn (yet) your Nobel prize or your retirement, it is unlikely you never heard about research metrics. These metrics aim at quantifying various aspects of the research process, at the level of individual researchers (e.g. h-index, altmetrics), scientific journals (e.g. impact factors) or entire universities/ countries (e.g. rankings). Although such "measurements" have existed in a simple form for a long time, their widespread calculation was enabled by the advent of the digital era (large amount of data available worldwide in a computer-compatible format). And in this new era, what becomes technically possible will be done, and what is done and appears to simplify our lives will be used. As a result, a rapidly growing number of statistics-based numerical indices are nowadays fed into decisionmaking processes. This is true in nearly all aspects of society (politics, economy, education and private life), and in particular in research, where metrics play an increasingly important role in determining positions, funding, awards, research programs, career choices, reputations, etc.

Content

Inhalt: Metrics in Research - For better or worse? / Jozica Dolenc, Philippe Hünenberger Oliver Renn - A brief visual history of research metrics / Oliver Renn, Jozica Dolenc, Joachim Schnabl - Bibliometry: The wizard of O's / Philippe Hünenberger - The grip of bibliometrics - A student perspective / Matthias Tinzl - Honesty and transparency to taxpayers is the long-term fundament for stable university funding / Wendelin J. Stark - Beyond metrics: Managing the performance of your work / Charlie Rapple - Scientific profiling instead of bibliometrics: Key performance indicators of the future / Rafael Ball - More knowledge, less numbers / Carl Philipp Rosenau - Do we really need BIBLIO-metrics to evaluate individual researchers? / Rüdiger Mutz - Using research metrics responsibly and effectively as a researcher / Peter I. Darroch, Lisa H. Colledge - Metrics in research: More (valuable) questions than answers / Urs Hugentobler - Publication of research results: Use and abuse / Wilfred F. van Gunsteren - Wanted: Transparent algorithms, interpretation skills, common sense / Eva E. Wille - Impact factors, the h-index, and citation hype - Metrics in research from the point of view of a journal editor / Renato Zenobi - Rashomon or metrics in a publisher's world / Gabriella Karger - The impact factor and I: A love-hate relationship / Jean-Christophe Leroux - Personal experiences bringing altmetrics to the academic market / Ben McLeish - Fatally attracted by numbers? / Oliver Renn - On computable numbers / Gerd Folkers, Laura Folkers - ScienceMatters - Single observation science publishing and linking observations to create an internet of science / Lawrence Rajendran.

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Abstract

Using citation data to assess research ultimately means using citation-based statistics to rank things.journals, papers, people, programs, and disciplines. The statistical tools used to rank these things are often misunderstood and misused. - For journals, the impact factor is most often used for ranking. This is a simple average derived from the distribution of citations for a collection of articles in the journal. The average captures only a small amount of information about that distribution, and it is a rather crude statistic. In addition, there are many confounding factors when judging journals by citations, and any comparison of journals requires caution when using impact factors. Using the impact factor alone to judge a journal is like using weight alone to judge a person's health. - For papers, instead of relying on the actual count of citations to compare individual papers, people frequently substitute the impact factor of the journals in which the papers appear. They believe that higher impact factors must mean higher citation counts. But this is often not the case! This is a pervasive misuse of statistics that needs to be challenged whenever and wherever it occurs. -For individual scientists, complete citation records can be difficult to compare. As a consequence, there have been attempts to find simple statistics that capture the full complexity of a scientist's citation record with a single number. The most notable of these is the h-index, which seems to be gaining in popularity. But even a casual inspection of the h-index and its variants shows that these are naive attempts to understand complicated citation records. While they capture a small amount of information about the distribution of a scientist's citations, they lose crucial information that is essential for the assessment of research.
The validity of statistics such as the impact factor and h-index is neither well understood nor well studied. The connection of these statistics with research quality is sometimes established on the basis of "experience." The justification for relying on them is that they are "readily available." The few studies of these statistics that were done focused narrowly on showing a correlation with some other measure of quality rather than on determining how one can best derive useful information from citation data. We do not dismiss citation statistics as a tool for assessing the quality of research.citation data and statistics can provide some valuable information. We recognize that assessment must be practical, and for this reason easily-derived citation statistics almost surely will be part of the process. But citation data provide only a limited and incomplete view of research quality, and the statistics derived from citation data are sometimes poorly understood and misused. Research is too important to measure its value with only a single coarse tool. We hope those involved in assessment will read both the commentary and the details of this report in order to understand not only the limitations of citation statistics but also how better to use them. If we set high standards for the conduct of science, surely we should set equally high standards for assessing its quality.

Content

Der vollständige Bericht ist im Internet unter der folgenden Adresse zugänglich: http://www.mathunion.org/fileadmin/IMU/Report/CitationStatistics.pdf. - Vgl. auch den Beitrag: Zitaten-Statistiken. In: Mitteilungen der Deutschen Mathematiker-Vereinigung. 2008, H.3, S.198-203.

Object

h-index