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Katy Börner, Adam H Simpson, Andreas Bueckle, Robert L Goldstone
Most maps of science use a network layout; few use a landscape metaphor. Human users are trained in reading geospatial maps, yet most have a hard time reading even simple networks. Prior work using general networks has shown that map-based visualizations increase recall accuracy of data. This paper reports the result of a comparison of two comparable renderings of the UCSD map of science that are: the original network layout and a novel hexmap that uses a landscape metaphor to layout the 554 subdisciplines grouped into 13 color-coded disciplines of science...
February 2018: Scientometrics
Nina Lykke
The article is an invited comment on Guy Madison and Therese Söderlund (M&S): Comparisons of content and scientific quality indicators across peer-reviewed journal articles with more or less gender perspective: Gender studies can do better. Scientometrics 115(3):1161-1183. The article pinpoints a series of serious problems in M&S's quantitative quality assessment and analysis of the field of gender studies, pertaining to their overall conceptual framework, their general approach and their specific analysis...
2018: Scientometrics
Christian Herzog, Brian Kierkegaard Lunn
With Dimensions, Digital Science provides the research community a new approach on research related information, bringing formerly siloed content types such as grants, patents, clinical trials with publications and citations together, making it as openly available as possible (see Due to the different content types, (controversial) journal based classifications were not an option since it would not allow to categorise grants etc. Hence Digital Science opted for applying a categorisation approach using machine learning and based on the content of the documents and well established classification systems for which a training set was available...
2018: Scientometrics
R Basurto-Flores, L Guzmán-Vargas, S Velasco, A Medina, A Calvo Hernandez
Our aim is to illustrate how the thermodynamics-based concept of entropy has spread across different areas of knowledge by analyzing the distribution of papers, citations and the use of words related to entropy in the predefined Scopus categories. To achieve this, we analyze the Scopus papers database related to entropy research during the last 20 years, collecting 750 K research papers which directly contain or mention the word entropy. First, some well-recognized works which introduced novel entropy-related definitions are monitored...
2018: Scientometrics
Balázs Győrffy, Andrea Magda Nagy, Péter Herman, Ádám Török
The Momentum program launched in 2009 provides funding of up to 1 million Euro to establish new, independent research groups at Hungarian academic institutions. Here, our aim was to determine factors associated with the scientific output of these research groups. Publication data were downloaded from the Hungarian Scientific Work Archive (, impact factor data were obtained from Thomson Reuters (, and journal ranks were extracted from the Scimago Journal Rank database (www...
2018: Scientometrics
Peter van den Besselaar, Ulf Sandström, Hélène Schiffbaenker
Peer and panel review are the dominant forms of grant decision-making, despite its serious weaknesses as shown by many studies. This paper contributes to the understanding of the grant selection process through a linguistic analysis of the review reports. We reconstruct in that way several aspects of the evaluation and selection process: what dimensions of the proposal are discussed during the process and how, and what distinguishes between the successful and non-successful applications? We combine the linguistic findings with interviews with panel members and with bibliometric performance scores of applicants...
2018: Scientometrics
Loet Leydesdorff
The dilemma which remained unsolved using Rao-Stirling diversity, namely of how variety and balance can be combined into "dual concept diversity" (Stirling in SPRU electronic working paper series no. 28., 1998, p. 48f.) can be clarified by using Nijssen et al.'s (Coenoses 13(1):33-38 1998) argument that the Gini coefficient is a perfect indicator of balance. However, the Gini coefficient is not an indicator of variety; this latter term can be operationalized independently as relative variety...
2018: Scientometrics
Francisco Grimaldo, Mario Paolucci, Jordi Sabater-Mir
We present an agent-based model of paper publication and consumption that allows to study the effect of two different evaluation mechanisms, peer review and reputation, on the quality of the manuscripts accessed by a scientific community. The model was empirically calibrated on two data sets, mono- and multi-disciplinary. Our results point out that disciplinary settings differ in the rapidity with which they deal with extreme events-papers that have an extremely high quality, that we call outliers. In the mono-disciplinary case, reputation is better than traditional peer review to optimize the quality of papers read by researchers...
2018: Scientometrics
Federico Bianchi, Francisco Grimaldo, Giangiacomo Bravo, Flaminio Squazzoni
This paper looks at peer review as a cooperation dilemma through a game-theory framework. We built an agent-based model to estimate how much the quality of peer review is influenced by different resource allocation strategies followed by scientists dealing with multiple tasks, i.e., publishing and reviewing. We assumed that scientists were sensitive to acceptance or rejection of their manuscripts and the fairness of peer review to which they were exposed before reviewing. We also assumed that they could be realistic or excessively over-confident about the quality of their manuscripts when reviewing...
2018: Scientometrics
Kevin Heffernan, Simone Teufel
Research is often described as a problem-solving activity, and as a result, descriptions of problems and solutions are an essential part of the scientific discourse used to describe research activity. We present an automatic classifier that, given a phrase that may or may not be a description of a scientific problem or a solution, makes a binary decision about problemhood and solutionhood of that phrase. We recast the problem as a supervised machine learning problem, define a set of 15 features correlated with the target categories and use several machine learning algorithms on this task...
2018: Scientometrics
Robin Haunschild, Lutz Bornmann
Thelwall (J Informetr 11(1):128-151, 2017a. 10.1016/j.joi.2016.12.002; Web indicators for research evaluation: a practical guide. Morgan and Claypool, London, 2017b) proposed a new family of field- and time-normalized indicators, which is intended for sparse data. These indicators are based on units of analysis (e.g., institutions) rather than on the paper level. They compare the proportion of mentioned papers (e.g., on Twitter) of a unit with the proportion of mentioned papers in the corresponding fields and publication years...
2018: Scientometrics
Takahiro Kawamura, Katsutaro Watanabe, Naoya Matsumoto, Shusaku Egami, Mari Jibu
Maps of science representing the structure of science can help us understand science and technology (S&T) development. Studies have thus developed techniques for analyzing research activities' relationships; however, ongoing research projects and recently published papers have difficulty in applying inter-citation and co-citation analysis. Therefore, in order to characterize what is currently being attempted in the scientific landscape, this paper proposes a new content-based method of locating research projects in a multi-dimensional space using the recent word/paragraph embedding techniques...
2018: Scientometrics
Lutz Bornmann, Adam Y Ye, Fred Y Ye
"Hot papers" (HPs) are papers which received a boost of citations shortly after publication. Papers with "delayed recognition" (DRs) received scarcely impact over a long time period, before a considerable citation boost started. DRs have attracted a lot of attention in scientometrics and beyond. Based on a comprehensive dataset with more than 5,000,000 papers published between 1980 and 1990, we identified HPs and DRs. In contrast to many other studies on DRs, which are based on raw citation counts, we calculated dynamically field-normalized impact scores for the search of HPs and DRs...
2018: Scientometrics
Rodrigo Costas, Thomas Franssen
In a recent Letter to the Editor Teixeira da Silva and Dobránszki (2018) present a discussion of the issues regarding the h-index as an indicator for the evaluation of individual scholars, particularly in the current landscape of the proliferation of online sources that provide individual level bibliometric indicators. From our point of view, the issues surrounding the h-index go far beyond the problems mentioned by TSD. In this letter we provide some overview of this, mostly by expanding TSD's original argument and discussing more conceptual and global issues related to the indicator, particularly in the outlook of a strong proliferation of online sources providing individual researcher indicators...
2018: Scientometrics
Lutz Bornmann, Loet Leydesdorff
Teixeira da Silva and Dobránszki (Scientometrics. 10.1007/s11192-018-2680-3, 2018) describe practical problems in using the h -index for the purpose of research evaluation. For example, they discuss the h -index differences among the bibliometric databases. In this Letter to the Editor, we argue for abstaining from using the h -index. One can use normalized indicators instead.
2018: Scientometrics
Alberto Falk Delgado, Anna Falk Delgado
Recently, in the four top journals of humanities, an institutional bias towards publication of authors from Harvard and Yale was shown. The New England Journal of Medicine (NEJM) is today the highest ranked general medical journal. It is unknown if there exists institutional bias favoring publication of articles originating from Harvard University, since the NEJM is produced by the Massachusetts Medical Society with close connections to the Harvard University. We examined if studies originating from the Harvard University published in the NEJM were noninferior in terms of citation rates compared to articles with an origin outside Harvard University...
2018: Scientometrics
Marek Kwiek
The growing scholarly interest in research top performers comes from the growing policy interest in research top performance itself. A question emerges: what makes someone a top performer? In this paper, the upper 10% of Polish academics in terms of research productivity are studied, and predictors of entering this class are sought. In the science system (and Poland follows global patterns), a small number of scholars produce most of the works and attract huge numbers of citations. Performance determines rewards, and small differences in talent translate into a disproportionate level of success, leading to inequalities in resources, research outcomes, and rewards...
2018: Scientometrics
Lutz Bornmann, Robin Haunschild
In research evaluation of single researchers, the assessment of paper and journal impact is of interest. High journal impact reflects the ability of researchers to convince strict reviewers, and high paper impact reflects the usefulness of papers for future research. In many bibliometric studies, metrics for journal and paper impact are separately presented. In this paper, we introduce two graph types, which combine both metrics in a single graph. The graphs can be used in research evaluation to visualize the performance of single researchers comprehensively...
2018: Scientometrics
Andi Rexha, Mark Kröll, Hermann Ziak, Roman Kern
The goal of our work is inspired by the task of associating segments of text to their real authors. In this work, we focus on analyzing the way humans judge different writing styles. This analysis can help to better understand this process and to thus simulate/ mimic such behavior accordingly. Unlike the majority of the work done in this field (i.e. authorship attribution, plagiarism detection, etc.) which uses content features, we focus only on the stylometric, i.e. content-agnostic, characteristics of authors...
2018: Scientometrics
Aleksandra Cislak, Magdalena Formanowicz, Tamar Saguy
The bias against women in academia is a documented phenomenon that has had detrimental consequences, not only for women, but also for the quality of science. First, gender bias in academia affects female scientists, resulting in their underrepresentation in academic institutions, particularly in higher ranks. The second type of gender bias in science relates to some findings applying only to male participants, which produces biased knowledge. Here, we identify a third potentially powerful source of gender bias in academia: the bias against research on gender bias...
2018: Scientometrics
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