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Ruediger Mutz

Publications and source records attributed to Ruediger Mutz.

14 recordsLinked to original sources
arXiv2021

The h-index

The h-index is a mainstream bibliometric indicator, since it is widely used in academia, research management and research policy. While its advantages have been highlighted, such as its simple calculation, it has also received widespread criticism. The criticism is mainly based on the negative effects it may have on scholars, when the index is used to describe the quality of a scholar. The "h" means "highly-cited" and "high achievement", and should not be confused with the last name of its inventor, Hirsch. Put simply, the h-index combines a measure of quantity and impact in a single indicator. Several initiatives try to provide alternatives to the h-index to counter some of its shortcomings.

cs.DL↗
arXiv2021

Growth rates of modern science: A latent piecewise growth curve approach to model publication numbers from established and new literature databases

Growth of science is a prevalent issue in science of science studies. In recent years, two new bibliographic databases have been introduced which can be used to study growth processes in science from centuries back: Dimensions from Digital Science and Microsoft Academic. In this study, we used publication data from these new databases and added publication data from two established databases (Web of Science from Clarivate Analytics and Scopus from Elsevier) to investigate scientific growth processes from the beginning of the modern science system until today. We estimated regression models that included simultaneously the publication counts from the four databases. The results of the unrestricted growth of science calculations show that the overall growth rate amounts to 4.10% with a doubling time of 17.3 years. As the comparison of various segmented regression models in the current study revealed, the model with five segments fits the publication data best. We demonstrated that these segments with different growth rates can be interpreted very well, since they are related to either phases of economic (e.g., industrialization) and / or political developments (e.g., Second World War). In this study, we additionally analyzed scientific growth in two broad fields (Physical and Technical Sciences as well as Life Sciences) and the relationship of scientific and economic growth in UK. The comparison between the two fields revealed only slight differences. The comparison of the British economic and scientific growth rates showed that the economic growth rate is slightly lower than the scientific growth rate.

cs.DL↗
arXiv2021

Mapping the impact of papers on various status groups: A new excellence mapping tool based on citation and reader scores

In over five years, Bornmann, Stefaner, de Moya Anegon, and Mutz (2014) and Bornmann, Stefaner, de Moya Anegon, and Mutz (2014, 2015) have published several releases of the www.excellencemapping.net tool revealing (clusters of) excellent institutions worldwide based on citation data. With the new release, a completely revised tool has been published. It is not only based on citation data (bibliometrics), but also Mendeley data (altmetrics). Thus, the institutional impact measurement of the tool has been expanded by focusing on additional status groups besides researchers such as students and librarians. Furthermore, the visualization of the data has been completely updated by improving the operability for the user and including new features such as institutional profile pages. In this paper, we describe the datasets for the current excellencemapping.net tool and the indicators applied. Furthermore, the underlying statistics for the tool and the use of the web application are explained.

cs.DL↗
arXiv2020

Should citations be field-normalized in evaluative bibliometrics? An empirical analysis based on propensity score matching

Field-normalization of citations is bibliometric standard. Despite the observed differences in citation counts between fields, the question remains how strong fields influence citation rates beyond the effect of attributes or factors possibly influencing citations (FICs). We considered several FICs such as number of pages and number of co-authors in this study. We wondered whether there is a separate field-effect besides other effects (e.g., from numbers of pages and co-authors). To find an answer on the question in this study, we applied inverse-probability of treatment weighting (IPW). Using Web of Science data (a sample of 308,231 articles), we investigated whether mean differences among subject categories in citation rates still remain, even if the subject categories are made comparable in the field-related attributes (e.g., comparable of co-authors, comparable number of pages) by IPW. In a diagnostic step of our statistical analyses, we considered propensity scores as covariates in regression analyses to examine whether the differences between the fields in FICs vanish. The results revealed that the differences did not completely vanish but were strongly reduced. We received similar results when we calculated mean value differences of the fields after IPW representing the causal or unconfounded field effects on citations. However, field differences in citation rates remain. The results point out that field-normalization seems to be a prerequisite for citation analysis and cannot be replaced by the consideration of any set of FICs in citation analyses.

cs.DL↗
arXiv2016

Excellence networks in science: A Web-based application based on Bayesian multilevel logistic regression (BMLR) for the identification of institutions collaborating successfully

In this study we present an application which can be accessed via www.excellence-networks.net and which represents networks of scientific institutions worldwide. The application is based on papers (articles, reviews and conference papers) published between 2007 and 2011. It uses (network) data, on which the SCImago Institutions Ranking is based (Scopus data from Elsevier). Using this data, institutional networks have been estimated with statistical models (Bayesian multilevel logistic regression, BMLR) for a number of Scopus subject areas. Within single subject areas, we have investigated and visualized how successfully overall an institution (reference institution) has collaborated (compared to all the other institutions in a subject area), and with which other institutions (network institutions) a reference institution has collaborated particularly successfully. The "best paper rate" (statistically estimated) was used as an indicator for evaluating the collaboration success of an institution. This gives the proportion of highly cited papers from an institution, and is considered generally as an indicator for measuring impact in bibliometrics.

cs.DL↗
arXiv2014

Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references

Many studies in information science have looked at the growth of science. In this study, we re-examine the question of the growth of science. To do this we (i) use current data up to publication year 2012 and (ii) analyse it across all disciplines and also separately for the natural sciences and for the medical and health sciences. Furthermore, the data are analysed with an advanced statistical technique - segmented regression analysis - which can identify specific segments with similar growth rates in the history of science. The study is based on two different sets of bibliometric data: (1) The number of publications held as source items in the Web of Science (WoS, Thomson Reuters) per publication year and (2) the number of cited references in the publications of the source items per cited reference year. We have looked at the rate at which science has grown since the mid-1600s. In our analysis of cited references we identified three growth phases in the development of science, which each led to growth rates tripling in comparison with the previous phase: from less than 1% up to the middle of the 18th century, to 2 to 3% up to the period between the two world wars and 8 to 9% to 2012.

cs.DL↗
arXiv2014

On the origins and the historical roots of the Higgs boson research from a bibliometric perspective

Subject of our present paper is the analysis of the origins or historical roots of the Higgs boson research from a bibliometric perspective, using a segmented regression analysis in a reference publication year spectroscopy (RPYS). Our analysis is based on the references cited in the Higgs boson publications published since 1974. The objective of our analysis consists of identifying concrete individual publications in the Higgs boson research context to which the scientific community frequently had referred to. As a consequence, we are interested in seminal works which contributed to a high extent to the discovery of the Higgs boson. Our results show that researchers in the Higgs boson field preferably refer to more recently published papers - particular papers published since the beginning of the sixties. For example, our analysis reveals seven major contributions which appeared within the sixties: Englert and Brout (1964), Higgs (1964, 2 papers), and Guralnik et al. (1964) on the Higgs mechanism as well as Glashow (1961), Weinberg (1967), and Salam (1968) on the unification of weak and electromagnetic interaction. Even if the Nobel Prize award highlights the outstanding importance of the work of Peter Higgs and Francois Englert, bibliometrics offer the additional possibility of getting hints to other publications in this research field (especially to historical publications), which are of vital importance from the expert point of view.

physics.hist-ph↗
arXiv2014

What is the effect of country-specific characteristics on the research performance of scientific institutions? Using multi-level statistical models to rank and map universities and research-focused institutions worldwide

Bornmann, Stefaner, de Moya Anegon, and Mutz (in press) have introduced a web application (www.excellencemapping.net) which is linked to both academic ranking lists published hitherto (e.g. the Academic Ranking of World Universities) as well as spatial visualization approaches. The web application visualizes institutional performance within specific subject areas as ranking lists and on custom tile-based maps. The new, substantially enhanced version of the web application and the multilevel logistic regression on which it is based are described in this paper. Scopus data were used which have been collected for the SCImago Institutions Ranking. Only those universities and research-focused institutions are considered that have published at least 500 articles, reviews and conference papers in the period 2006 to 2010 in a certain Scopus subject area. In the enhanced version, the effect of single covariates (such as the per capita GDP of a country in which an institution is located) on two performance metrics (best paper rate and best journal rate) is examined and visualized. A covariate-adjusted ranking and mapping of the institutions is produced in which the single covariates are held constant. The results on the performance of institutions can then be interpreted as if the institutions all had the same value (reference point) for the covariate in question. For example, those institutions can be identified worldwide showing a very good performance despite a bad financial situation in the corresponding country.

cs.DL↗
arXiv2013

Ranking and mapping of universities and research-focused institutions worldwide based on highly-cited papers: A visualization of results from multi-level models

The web application presented in this paper allows for an analysis to reveal centres of excellence in different fields worldwide using publication and citation data. Only specific aspects of institutional performance are taken into account and other aspects such as teaching performance or societal impact of research are not considered. Based on data gathered from Scopus, field-specific excellence can be identified in institutions where highly-cited papers have been frequently published. The web application combines both a list of institutions ordered by different indicator values and a map with circles visualizing indicator values for geocoded institutions. Compared to the mapping and ranking approaches introduced hitherto, our underlying statistics (multi-level models) are analytically oriented by allowing (1) the estimation of values for the number of excellent papers for an institution which are statistically more appropriate than the observed values; (2) the calculation of confidence intervals as measures of accuracy for the institutional citation impact; (3) the comparison of a single institution with an "average" institution in a subject area, and (4) the direct comparison of at least two institutions.

cs.DL↗
arXiv2012

The use of percentiles and percentile rank classes in the analysis of bibliometric data: Opportunities and limits

Percentiles have been established in bibliometrics as an important alternative to mean-based indicators for obtaining a normalized citation impact of publications. Percentiles have a number of advantages over standard bibliometric indicators used frequently: for example, their calculation is not based on the arithmetic mean which should not be used for skewed bibliometric data. This study describes the opportunities and limits and the advantages and disadvantages of using percentiles in bibliometrics. We also address problems in the calculation of percentiles and percentile rank classes for which there is not (yet) a satisfactory solution. It will be hard to compare the results of different percentile-based studies with each other unless it is clear that the studies were done with the same choices for percentile calculation and rank assignment.

cs.DL↗
arXiv2009

New approaches for increasing the reliability of the h index research performance measurement

In the year 2005 Jorge Hirsch introduced the h index for quantifying the research output of scientists. Today, the h index is a widely accepted indicator of research performance. The h index has been criticized for its insufficient reliability - the ability to discriminate reliably between meaningful amounts of research performance. Taking as an example an extensive data set with bibliometric data on scientists working in the field of molecular biology, we compute h2 lower, h2 upper, and sRM values and present them as complementary approaches that improve the reliability of the h index research performance measurement.

stat.AP↗
arXiv2007

Gender differences in grant peer review: A meta-analysis

Narrative reviews of peer review research have concluded that there is negligible evidence of gender bias in the awarding of grants based on peer review. Here, we report the findings of a meta-analysis of 21 studies providing, to the contrary, evidence of robust gender differences in grant award procedures. Even though the estimates of the gender effect vary substantially from study to study, the model estimation shows that all in all, among grant applicants men have statistically significant greater odds of receiving grants than women by about 7%.

math.ST↗
arXiv2006

Latent Markov modelling applied to grant peer review

In the grant peer review process we can distinguish various evaluation stages in which assessors judge applications on a rating scale. Research on this process that considers its multi-stage character scarcely exists. In this study we analyze 1954 applications for doctoral and post-doctoral fellowships of the Boehringer Ingelheim Fonds (B.I.F.), assessed in three stages (first: evaluation by an external reviewer; second: internal evaluation by a staff member; third: final decision by the B.I.F. Board of Trustees). The results show that an application only has a chance of approval if it was recommended for support in the first evaluation stage. Therefore, a form of triage or pre-screening seems desirable. We found differences in transition probabilities from one stage to the other for doctoral applicants submitted by males and females.

math.ST↗