Search (65 results, page 1 of 4)

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Abstract

Scientists and managers using citation-based indicators to help evaluate research cannot evaluate recent articles because of the time needed for citations to accrue. Reading occurs before citing, however, and so it makes sense to count readers rather than citations for recent publications. To assess this, Mendeley readers and citations were obtained for articles from 2004 to late 2014 in five broad categories (agriculture, business, decision science, pharmacy, and the social sciences) and 50 subcategories. In these areas, citation counts tended to increase with every extra year since publication, and readership counts tended to increase faster initially but then stabilize after about 5 years. The correlation between citations and readers was also higher for longer time periods, stabilizing after about 5 years. Although there were substantial differences between broad fields and smaller differences between subfields, the results confirm the value of Mendeley reader counts as early scientific impact indicators.

Date

16.11.2016 11:07:22

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Abstract

Bioinformatics is a fast-growing field based on the optimal use of "big data" gathered in genomic, proteomics, and functional genomics research. In this paper, we conduct a comprehensive and in-depth bibliometric analysis of the field of bioinformatics by extracting citation data from PubMed Central full-text. Citation data for the period 2000 to 2011, comprising 20,869 papers with 546,245 citations, was used to evaluate the productivity and influence of this emerging field. Four measures were used to identify productivity; most productive authors, most productive countries, most productive organizations, and most popular subject terms. Research impact was analyzed based on the measures of most cited papers, most cited authors, emerging stars, and leading organizations. Results show the overall trends between the periods 2000 to 2003 and 2004 to 2007 were dissimilar, while trends between the periods 2004 to 2007 and 2008 to 2011 were similar. In addition, the field of bioinformatics has undergone a significant shift, co-evolving with other biomedical disciplines.

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Date

18. 3.2014 19:13:22

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Abstract

The aim of this paper is to visualize the history of evidence-based medicine (EBM) and to examine the characteristics of EBM development in China and the West. We searched the Web of Science and the Chinese National Knowledge Infrastructure database for papers related to EBM. We applied information visualization techniques, citation analysis, cocitation analysis, cocitation cluster analysis, and network analysis to construct historiographies, themes networks, and chronological theme maps regarding EBM in China and the West. EBM appeared to develop in 4 stages: incubation (1972-1992 in the West vs. 1982-1999 in China), initiation (1992-1993 vs. 1999-2000), rapid development (1993-2000 vs. 2000-2004), and stable distribution (2000 onwards vs. 2004 onwards). Although there was a lag in EBM initiation in China compared with the West, the pace of development appeared similar. Our study shows that important differences exist in research themes, domain structures, and development depth, and in the speed of adoption between China and the West. In the West, efforts in EBM have shifted from education to practice, and from the quality of evidence to its translation. In China, there was a similar shift from education to practice, and from production of evidence to its translation. In addition, this concept has diffused to other healthcare areas, leading to the development of evidence-based traditional Chinese medicine, evidence-based nursing, and evidence-based policy making.

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Abstract

This study presents a large-scale analysis of the distribution and presence of Mendeley readership scores over time and across disciplines. We study whether Mendeley readership scores (RS) can identify highly cited publications more effectively than journal citation scores (JCS). Web of Science (WoS) publications with digital object identifiers (DOIs) published during the period 2004-2013 and across five major scientific fields were analyzed. The main result of this study shows that RS are more effective (in terms of precision/recall values) than JCS to identify highly cited publications across all fields of science and publication years. The findings also show that 86.5% of all the publications are covered by Mendeley and have at least one reader. Also, the share of publications with Mendeley RS is increasing from 84% in 2004 to 89% in 2009, and decreasing from 88% in 2010 to 82% in 2013. However, it is noted that publications from 2010 onwards exhibit on average a higher density of readership versus citation scores. This indicates that compared to citation scores, RS are more prevalent for recent publications and hence they could work as an early indicator of research impact. These findings highlight the potential and value of Mendeley as a tool for scientometric purposes and particularly as a relevant tool to identify highly cited publications.

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Abstract

The goal of the study was to determine the underlying processes leading to the observed collaborator distribution in modern scientific fields, with special attention to nonpower-law behavior. Nanoscience is used as a case study of a modern interdisciplinary field and its coauthorship network for 2000-2004 period is constructed from the NanoBank database. We find three collaboration modes that correspond to three distinct ranges in the distribution of collaborators: (1) for authors with fewer than 20 collaborators (the majority) preferential attachment does not hold and they form a log-normal hook instead of a power law; (2) authors with more than 20 collaborators benefit from preferential attachment and form a power law tail; and (3) authors with between 250 and 800 collaborators are more frequent than expected because of the hyperauthorship practices in certain subfields.

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Abstract

Flattery citations of editors, potential referees, and so on have been claimed to be a common strategy among academic authors. From a sociology of science perspective as well as from a citation analytical perspective, it is both an interesting claim and a consequential one. The article presents a citation analysis of the editorial board members entering the American Economic Review from 1984 to 2004 using a citation window of 11 years. To test the flattery citation hypothesis further, we have conducted a study applying the difference-in-differences estimator. We analyze the number of times the editors and editorial board members of the American Economic Review were cited in articles published in the journal itself as well as in a pool of documents comprising articles from the Journal of Political Economy and the Quarterly Journal of Economics. The results of the analyses do not support the existence of a flattery citation effect.

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Abstract

The growing complexity of challenges involved in scientific progress demands ever more frequent application of competencies and knowledge from different scientific fields. The present work analyzes the degree of collaboration among scientists from different disciplines to identify the most frequent "combinations of knowledge" in research activity. The methodology adopts an innovative bibliometric approach based on the disciplinary affiliation of publication coauthors. The field of observation includes all publications (167,179) indexed in the Science Citation Index Expanded for the years 2004-2008, authored by all scientists in the hard sciences (43,223) at Italian universities (68). The analysis examines 205 research fields grouped in 9 disciplines. Identifying the fields with the highest potential of interdisciplinary collaboration is useful to inform research polices at the national and regional levels, as well as management strategies at the institutional level.

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Abstract

The 2004-2010 VQR (Research Quality Evaluation), completed in July 2013, was Italy's second national research assessment exercise. The VQR performance evaluation followed a pattern also seen in other nations, as it was based on a selected subset of products. In this work, we identify the exercise's methodological weaknesses and measure the distortions that result from them in the university performance rankings. First, we create a scenario in which we assume the efficient selection of the products to be submitted by the universities and, from this, simulate a set of rankings applying the precise VQR rating criteria. Next, we compare these "VQR rankings" with those that would derive from the application of more-appropriate bibliometrics. Finally, we extend the comparison to university rankings based on the entire scientific production for the period, as indexed in the Web of Science.

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Date

22. 1.2017 17:12:50

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Date

22. 8.2014 17:05:18

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Date

20. 1.2019 11:22:31

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Abstract

In the past several years studies have started to appear comparing the accuracies of various science mapping approaches. These studies primarily compare the cluster solutions resulting from different similarity approaches, and give varying results. In this study we compare the accuracies of cluster solutions of a large corpus of 2,153,769 recent articles from the biomedical literature (2004-2008) using four similarity approaches: co-citation analysis, bibliographic coupling, direct citation, and a bibliographic coupling-based citation-text hybrid approach. Each of the four approaches can be considered a way to represent the research front in biomedicine, and each is able to successfully cluster over 92% of the corpus. Accuracies are compared using two metrics-within-cluster textual coherence as defined by the Jensen-Shannon divergence, and a concentration measure based on the grant-to-article linkages indexed in MEDLINE. Of the three pure citation-based approaches, bibliographic coupling slightly outperforms co-citation analysis using both accuracy measures; direct citation is the least accurate mapping approach by far. The hybrid approach improves upon the bibliographic coupling results in all respects. We consider the results of this study to be robust given the very large size of the corpus, and the specificity of the accuracy measures used.

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Abstract

How can citation analysis take into account the highly collaborative nature and unique research and publication culture of biomedical research fields? This study explores this question by introducing last-author citation counting and comparing it with traditional first-author counting and theoretically optimal all-author counting in the stem cell research field for the years 2004-2009. For citation ranking, last-author counting, which is directly supported by Scopus but not by ISI databases, appears to approximate all-author counting quite well in a field where heads of research labs are traditionally listed as last authors; however, first author counting does not. For field mapping, we find that author co-citation analyses based on different counting methods all produce similar overall intellectual structures of a research field, but detailed structures and minor specialties revealed differ to various degrees and thus require great caution to interpret. This is true especially when authors are selected into the analysis based on citedness, because author selection is found to have a greater effect on mapping results than does choice of co-citation counting method. Findings are based on a comprehensive, high-quality dataset extracted in several steps from PubMed and Scopus and subjected to automatic reference and author name disambiguation.

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Abstract

In this article, we explore how strongly author name disambiguation (AND) affects the results of an author-based citation analysis study, and identify conditions under which the traditional simplified approach of using surnames and first initials may suffice in practice. We compare author citation ranking and cocitation mapping results in the stem cell research field from 2004 to 2009 using two AND approaches: the traditional simplified approach of using author surname and first initial and a sophisticated algorithmic approach. We find that the traditional approach leads to extremely distorted rankings and substantially distorted mappings of authors in this field when based on first- or all-author citation counting, whereas last-author-based citation ranking and cocitation mapping both appear relatively immune to the author name ambiguity problem. This is largely because Romanized names of Chinese and Korean authors, who are very active in this field, are extremely ambiguous, but few of these researchers consistently publish as last authors in bylines. We conclude that a more earnest effort is required to deal with the author name ambiguity problem in both citation analysis and information retrieval, especially given the current trend toward globalization. In the stem cell research field, in which laboratory heads are traditionally listed as last authors in bylines, last-author-based citation ranking and cocitation mapping using the traditional approach to author name disambiguation may serve as a simple workaround, but likely at the price of largely filtering out Chinese and Korean contributions to the field as well as important contributions by young researchers.

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Abstract

In this paper we analyze a major part of the research output of the Networked Knowledge Organization Systems (NKOS) community in the period 2000 to 2015 from a network analytical perspective. We fo- cus on the paper output presented at the European NKOS workshops in the last 15 years. Our open dataset, the "NKOS bibliography", includes 14 workshop agendas (ECDL 2000-2010, TPDL 2011-2015) and 4 special issues on NKOS (2001, 2004, 2006 and 2015) which cover 171 papers with 218 distinct authors in total. A focus of the analysis is the visualization of co-authorship networks in this interdisciplinary eld. We used standard network analytic measures like degree and betweenness centrality to de- scribe the co-authorship distribution in our NKOS dataset. We can see in our dataset that 15% (with degree=0) of authors had no co-authorship with others and 53% of them had a maximum of 3 cooperations with other authors. 32% had at least 4 co-authors for all of their papers. The NKOS co-author network in the "NKOS bibliography" is a typical co- authorship network with one relatively large component, many smaller components and many isolated co-authorships or triples.

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Source

Journal of the Association for Information Science and Technology. 68(2017) no.8, S.2004-2016

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Abstract

This study compares the 45 "Best Paper" award articles with nonaward articles published in the Journal of Association for Information Science and Technology (JASIST) to observe the differences in citations. The results show that, in most cases, the citations of the award articles are more numerous than the median, belonging to the Top-50% stratum. Only 15.6% of the award articles have the status of being the most-cited article of the year in which the article was published; 24.4% belong to the Top-5% stratum of the publication year; 44.4% belong to the Top-10% stratum of the publication year; and 73.3% belong to the Top-25% stratum of the publication year. Surprisingly, from 2000 to 2012, none of the award articles made it to the Top-10% stratum, apart from the year 2004; the least-cited award article received only three citations during a 5-year period. The results show a wide range of citations among the Best JASIST Papers. This study also observes that the number of articles changed little from 1969 to 1995 but grew rapidly from 1996 to 2012. Suggestions for possible ways to better meet the challenges of the journal's growth in size and scope in selecting award articles are provided.

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Abstract

This article studies the impact of differences in citation practices at the subfield, or Web of Science subject category level, using the model introduced in Crespo, Li, and Ruiz-Castillo (2013a), according to which the number of citations received by an article depends on its underlying scientific influence and the field to which it belongs. We use the same Thomson Reuters data set of about 4.4 million articles used in Crespo et al. (2013a) to analyze 22 broad fields. The main results are the following: First, when the classification system goes from 22 fields to 219 subfields the effect on citation inequality of differences in citation practices increases from ?14% at the field level to 18% at the subfield level. Second, we estimate a set of exchange rates (ERs) over a wide [660, 978] citation quantile interval to express the citation counts of articles into the equivalent counts in the all-sciences case. In the fractional case, for example, we find that in 187 of 219 subfields the ERs are reliable in the sense that the coefficient of variation is smaller than or equal to 0.10. Third, in the fractional case the normalization of the raw data using the ERs (or subfield mean citations) as normalization factors reduces the importance of the differences in citation practices from 18% to 3.8% (3.4%) of overall citation inequality. Fourth, the results in the fractional case are essentially replicated when we adopt a multiplicative approach.

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Date

26.10.2014 20:22:22