Bibliometric data in clinical cardiology revisited. The case of 37 Dutch professors

In this paper, we assess the bibliometric parameters of 37 Dutch professors in clinical cardiology. Those are the Hirsch index (h-index) based on all papers, the h-index based on first authored papers, the number of papers, the number of citations and the citations per paper. A top 10 for each of the five parameters was compiled. In theory, the same 10 professors might appear in each of these top 10s. Alternatively, each of the 37 professors under assessment could appear one or more times. In practice, we found 22 out of these 37 professors in the 5 top 10s. Thus, there is no golden parameter. In addition, there is too much inhomogeneity in citation characteristics even within a relatively homogeneous group of clinical cardiologists. Therefore, citation analysis should be applied with great care in science policy. This is even more important when different fields of medicine are compared in university medical centres. It may be possible to develop better parameters in the future, but the present ones are simply not good enough. Also, we observed a quite remarkable explosion of publications per author which can, paradoxical as it may sound, probably not be interpreted as an increase in productivity of scientists, but as the effect of an increase in the number of co-authors and the strategic effect of networks

A comment to the paper by Waltman et al., Scientometrics, 87, 467–481, 2011

In reaction to a previous critique (Opthof and Leydesdorff, J Informetr 4(3):423–430, 2010), the Center for Science and Technology Studies (CWTS) in Leiden proposed to change their old “crown” indicator in citation analysis into a new one. Waltman (Scientometrics 87:467–481, 2011a) argue that this change does not affect rankings at various aggregated levels. However, CWTS data is not publicly available for testing and criticism. Therefore, we comment by using previously published data of Van Raan (Scientometrics 67(3):491–502, 2006) to address the pivotal issue of how the results of citation analysis correlate with the results of peer review. A quality parameter based on peer review was neither significantly correlated with the two parameters developed by the CWTS in the past citations per paper/mean journal citation score (CPP/JCSm) or CPP/FCSm (citations per paper/mean field citation score) nor with the more recently proposed h-index (Hirsch, Proc Natl Acad Sci USA 102(46):16569–16572, 2005). Given the high correlations between the old and new “crown” indicators, one can expect that the lack of correlation with the peer-review based quality indicator applies equally to the newly developed ones

The Citation Field of Evolutionary Economics

Evolutionary economics has developed into an academic field of its own, institutionalized around, amongst others, the Journal of Evolutionary Economics (JEE). This paper analyzes the way and extent to which evolutionary economics has become an interdisciplinary journal, as its aim was: a journal that is indispensable in the exchange of expert knowledge on topics and using approaches that relate naturally with it. Analyzing citation data for the relevant academic field for the Journal of Evolutionary Economics, we use insights from scientometrics and social network analysis to find that, indeed, the JEE is a central player in this interdisciplinary field aiming mostly at understanding technological and regional dynamics. It does not, however, link firmly with the natural sciences (including biology) nor to management sciences, entrepreneurship, and organization studies. Another journal that could be perceived to have evolutionary acumen, the Journal of Economic Issues, does relate to heterodox economics journals and is relatively more involved in discussing issues of firm and industry organization. The JEE seems most keen to develop theoretical insights

A reverse engineering approach to the suppression of citation biases reveals universal properties of citation distributions

The large amount of information contained in bibliographic databases has recently boosted the use of citations, and other indicators based on citation numbers, as tools for the quantitative assessment of scientific research. Citations counts are often interpreted as proxies for the scientific influence of papers, journals, scholars, and institutions. However, a rigorous and scientifically grounded methodology for a correct use of citation counts is still missing. In particular, cross-disciplinary comparisons in terms of raw citation counts systematically favors scientific disciplines with higher citation and publication rates. Here we perform an exhaustive study of the citation patterns of millions of papers, and derive a simple transformation of citation counts able to suppress the disproportionate citation counts among scientific domains. We find that the transformation is well described by a power-law function, and that the parameter values of the transformation are typical features of each scientific discipline. Universal properties of citation patterns descend therefore from the fact that citation distributions for papers in a specific field are all part of the same family of univariate distributions.Comment: 9 pages, 6 figures. Supporting information files available at http://filrad.homelinux.or

Characterizing a scientific elite: the social characteristics of the most highly cited scientists in environmental science and ecology

In science, a relatively small pool of researchers garners a disproportionally large number of citations. Still, very little is known about the social characteristics of highly cited scientists. This is unfortunate as these researchers wield a disproportional impact on their fields, and the study of highly cited scientists can enhance our understanding of the conditions which foster highly cited work, the systematic social inequalities which exist in science, and scientific careers more generally. This study provides information on this understudied subject by examining the social characteristics and opinions of the 0.1% most cited environmental scientists and ecologists. Overall, the social characteristics of these researchers tend to reflect broader patterns of inequality in the global scientific community. However, while the social characteristics of these researchers mirror those of other scientific elites in important ways, they differ in others, revealing findings which are both novel and surprising, perhaps indicating multiple pathways to becoming highly cited

Tracing scientist's research trends realtimely

In this research, we propose a method to trace scientists' research trends realtimely. By monitoring the downloads of scientific articles in the journal of Scientometrics for 744 hours, namely one month, we investigate the download statistics. Then we aggregate the keywords in these downloaded research papers, and analyze the trends of article downloading and keyword downloading. Furthermore, taking both the download of keywords and articles into consideration, we design a method to detect the emerging research trends. We find that in scientometrics field, social media, new indices to quantify scientific productivity (g-index), webometrics, semantic, text mining, open access are emerging fields that scientometrics researchers are focusing on.Comment: 13 pages, 7 figure

Effectiveness of Journal Ranking Schemes as a Tool for Locating Information

BACKGROUND: The rise of electronic publishing, preprint archives, blogs, and wikis is raising concerns among publishers, editors, and scientists about the present day relevance of academic journals and traditional peer review. These concerns are especially fuelled by the ability of search engines to automatically identify and sort information. It appears that academic journals can only remain relevant if acceptance of research for publication within a journal allows readers to infer immediate, reliable information on the value of that research. METHODOLOGY/PRINCIPAL FINDINGS: Here, we systematically evaluate the effectiveness of journals, through the work of editors and reviewers, at evaluating unpublished research. We find that the distribution of the number of citations to a paper published in a given journal in a specific year converges to a steady state after a journal-specific transient time, and demonstrate that in the steady state the logarithm of the number of citations has a journal-specific typical value. We then develop a model for the asymptotic number of citations accrued by papers published in a journal that closely matches the data. CONCLUSIONS/SIGNIFICANCE: Our model enables us to quantify both the typical impact and the range of impacts of papers published in a journal. Finally, we propose a journal-ranking scheme that maximizes the efficiency of locating high impact research

A small world of citations? The influence of collaboration networks on citation practices

This paper examines the proximity of authors to those they cite using degrees of separation in a co-author network, essentially using collaboration networks to expand on the notion of self-citations. While the proportion of direct self-citations (including co-authors of both citing and cited papers) is relatively constant in time and across specialties in the natural sciences (10% of citations) and the social sciences (20%), the same cannot be said for citations to authors who are members of the co-author network. Differences between fields and trends over time lie not only in the degree of co-authorship which defines the large-scale topology of the collaboration network, but also in the referencing practices within a given discipline, computed by defining a propensity to cite at a given distance within the collaboration network. Overall, there is little tendency to cite those nearby in the collaboration network, excluding direct self-citations. By analyzing these social references, we characterize the social capital of local collaboration networks in terms of the knowledge production within scientific fields. These results have implications for the long-standing debate over biases common to most types of citation analysis, and for understanding citation practices across scientific disciplines over the past 50 years. In addition, our findings have important practical implications for the availability of 'arm's length' expert reviewers of grant applications and manuscripts

Genetic Differentiation, Structure, and a Transition Zone among Populations of the Pitcher Plant Moth Exyra semicrocea: Implications for Conservation

Pitcher plant bogs, or carnivorous plant wetlands, have experienced extensive habitat loss and fragmentation throughout the southeastern United States Coastal Plain, resulting in an estimated reduction to <3% of their former range. This situation has lead to increased management attention of these habitats and their carnivorous plant species. However, conservation priorities focus primarily on the plants since little information currently exists on other community members, such as their endemic arthropod biota. Here, we investigated the population structure of one of these, the obligate pitcher plant moth Exyra semicrocea (Lepidoptera: Noctuidae), using mitochondrial cytochrome c oxidase subunit I (COI) gene sequences. Examination of 221 individuals from 11 populations across eight southeastern US states identified 51 unique haplotypes. These haplotypes belonged to one of two divergent (∼1.9–3.0%) lineages separated by the Mississippi alluvial plain. Populations of the West Gulf Coastal Plain exhibited significant genetic structure, contrasting with similarly distanced populations east of the Mississippi alluvial plain. In the eastern portion of the Coastal Plain, an apparent transition zone exists between two regionally distinct population groups, with a well-established genetic discontinuity for other organisms coinciding with this zone. The structure of E. semicrocea appears to have been influenced by patchy pitcher plant bog habitats in the West Gulf Coastal Plain as well as impacts of Pleistocene interglacials on the Apalachicola-Chattahoochee-Flint River Basin. These findings, along with potential extirpation of E. semicrocea at four visited, but isolated, sites highlight the need to consider other endemic or associated community members when managing and restoring pitcher plant bog habitats

Using Noun Phrases for Navigating Biomedical Literature on Pubmed: How Many Updates Are We Losing Track of?

Author-supplied citations are a fraction of the related literature for a paper. The “related citations” on PubMed is typically dozens or hundreds of results long, and does not offer hints why these results are related. Using noun phrases derived from the sentences of the paper, we show it is possible to more transparently navigate to PubMed updates through search terms that can associate a paper with its citations. The algorithm to generate these search terms involved automatically extracting noun phrases from the paper using natural language processing tools, and ranking them by the number of occurrences in the paper compared to the number of occurrences on the web. We define search queries having at least one instance of overlap between the author-supplied citations of the paper and the top 20 search results as citation validated (CV). When the overlapping citations were written by same authors as the paper itself, we define it as CV-S and different authors is defined as CV-D. For a systematic sample of 883 papers on PubMed Central, at least one of the search terms for 86% of the papers is CV-D versus 65% for the top 20 PubMed “related citations.” We hypothesize these quantities computed for the 20 million papers on PubMed to differ within 5% of these percentages. Averaged across all 883 papers, 5 search terms are CV-D, and 10 search terms are CV-S, and 6 unique citations validate these searches. Potentially related literature uncovered by citation-validated searches (either CV-S or CV-D) are on the order of ten per paper – many more if the remaining searches that are not citation-validated are taken into account. The significance and relationship of each search result to the paper can only be vetted and explained by a researcher with knowledge of or interest in that paper