An extensive analysis of the presence of altmetric data for Web of Science publications across subject fields and research topics.

Sufficient data presence is one of the key preconditions for applying metrics in practice. Based on both Altmetric.com data and Mendeley data collected up to 2019, this paper presents a state-of-the-art analysis of the presence of 12 kinds of altmetric events for nearly 12.3 million Web of Science publications published between 2012 and 2018. Results show that even though an upward trend of data presence can be observed over time, except for Mendeley readers and Twitter mentions, the overall presence of most altmetric data is still low. The majority of altmetric events go to publications in the fields of Biomedical and Health Sciences, Social Sciences and Humanities, and Life and Earth Sciences. As to research topics, the level of attention received by research topics varies across altmetric data, and specific altmetric data show different preferences for research topics, on the basis of which a framework for identifying hot research topics is proposed and applied to detect research topics with higher levels of attention garnered on certain altmetric data source. Twitter mentions and policy document citations were selected as two examples to identify hot research topics of interest of Twitter users and policy-makers, respectively, shedding light on the potential of altmetric data in monitoring research trends of specific social attention.

From Eminent Men to Excellent Universities: University Rankings as Calculative Devices.

Global university rankings have become increasingly important 'calculative devices' for assessing the 'quality' of higher education and research. Their ability to make characteristics of universities 'calculable' is here exemplified by the first proper university ranking ever, produced as early as 1910 by the American psychologist James McKeen Cattell. Our paper links the epistemological rationales behind the construction of this ranking to the sociopolitical context in which Cattell operated: an era in which psychology became institutionalized against the backdrop of the eugenics movement, and in which statistics of science became used to counter a perceived decline in 'great men.' Over time, however, the 'eminent man,' shaped foremost by heredity and upbringing, came to be replaced by the excellent university as the emblematic symbol of scientific and intellectual strength. We also show that Cattell's ranking was generative of new forms of the social, traces of which can still be found today in the enactment of 'excellence' in global university rankings.

Professional and citizen bibliometrics: complementarities and ambivalences in the development and use of indicators-a state-of-the-art report.

Bibliometric indicators such as journal impact factors, h-indices, and total citation counts are algorithmic artifacts that can be used in research evaluation and management. These artifacts have no meaning by themselves, but receive their meaning from attributions in institutional practices. We distinguish four main stakeholders in these practices: (1) producers of bibliometric data and indicators; (2) bibliometricians who develop and test indicators; (3) research managers who apply the indicators; and (4) the scientists being evaluated with potentially competing career interests. These different positions may lead to different and sometimes conflicting perspectives on the meaning and value of the indicators. The indicators can thus be considered as boundary objects which are socially constructed in translations among these perspectives. This paper proposes an analytical clarification by listing an informed set of (sometimes unsolved) problems in bibliometrics which can also shed light on the tension between simple but invalid indicators that are widely used (e.g., the h-index) and more sophisticated indicators that are not used or cannot be used in evaluation practices because they are not transparent for users, cannot be calculated, or are difficult to interpret.

Citation Metrics: A Primer on How (Not) to Normalize.

Citation metrics are increasingly used to appraise published research. One challenge is whether and how to normalize these metrics to account for differences across scientific fields, age (year of publication), type of document, database coverage, and other factors. We discuss the pros and cons for normalizations using different approaches. Additional challenges emerge when citation metrics need to be combined across multiple papers to appraise the corpus of scientists, institutions, journals, or countries, as well as when trying to attribute credit in multiauthored papers. Different citation metrics may offer complementary insights, but one should carefully consider the assumptions that underlie their calculation.

Bibliometric analysis of output and impact based on CRIS data: a case study on the registered output of a Dutch university.

In this study we combine the registered output of a whole university in the Netherlands with data retrieved from the Web of Science. The initial research question was: is it possible to show the impact of the university in its' full broadness, taking into account the variety of disciplines covered in the research profile of the university? In order to answer this question, we analyzed the output of the university as registered in the CRIS system METIS, over the years 2004-2009. The registration covers a wide variety of scholarly outputs, and these are all taken into account in the analysis. In the study we conduct analyses on the coverage of the output of the university, both from the perspective of the output itself, towards the Web of Science ("external"), as well as from the Web of Science perspective itself ("internal"). This provides us with the necessary information to be able to draw clear conclusions on the validity of the usage of standard bibliometric methodologies in the research assessment of universities with such a research profile.

[Publication pressure and citation stress; the influence of achievement indicators on scientific practice]. / Publicatiedrang en citatiestress; de invloed van prestatie-indicatoren op wetenschapsbeoefening.

The journal impact factor (JIF) and the Hirsch index, are two widely used parameters for evaluating scientific achievement. The JIF is a parameter which shows the citation score of a journal over the previous two years. The Hirsch index is a simple index to measure the citation performance of individual scientists. These achievement indicators can be used to evaluate research and are thus an indicator for scientific output. Nevertheless, they should not be used as a measurement of scientific quality. Scientific quality not only depends on citation scores, but also on originality, societal and scientific impact, robust methodology and validity and should therefore be evaluated on these parameters. Little is known about the influence that these factors have on science in general and on scientists but there is some evidence suggesting detrimental effects on scientific practice and quality.

Translating upwards: linking the neural and social sciences via neuroeconomics.

The social and neural sciences share a common interest in understanding the mechanisms that underlie human behaviour. However, interactions between neuroscience and social science disciplines remain strikingly narrow and tenuous. We illustrate the scope and challenges for such interactions using the paradigmatic example of neuroeconomics. Using quantitative analyses of both its scientific literature and the social networks in its intellectual community, we show that neuroeconomics now reflects a true disciplinary integration, such that research topics and scientific communities with interdisciplinary span exert greater influence on the field. However, our analyses also reveal key structural and intellectual challenges in balancing the goals of neuroscience with those of the social sciences. To address these challenges, we offer a set of prescriptive recommendations for directing future research in neuroeconomics.