Search (7 results, page 1 of 1)

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Abstract

The representation of science as a citation density landscape and the study of scaling rules with the field-specific citation density as a main topological property was previously analyzed at the level of research groups. Here, the focus is on the individual researcher. In this new analysis, the size dependence of several main bibliometric indicators for a large set of individual researchers is explored. Similar results as those previously observed for research groups are described for individual researchers. The total number of citations received by scientists increases in a cumulatively advantageous way as a function of size (in terms of number of publications) for researchers in three areas: Natural Resources, Biology & Biomedicine, and Materials Science. This effect is stronger for researchers in low citation density fields. Differences found among thematic areas with different citation densities are discussed.

Date

22. 3.2009 19:02:48

Footnote

Vgl. auch: Raan, A.F.J. van: Scaling rules in the science system: influence of field-specific citation characteristics on the impact of research groups. In: Journal of the American Society for Information Science and Technology. 59(2008) no.4, S.565-576.

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Abstract

Purpose - The purpose of this paper is to analyze the disciplinary orientation of scientific publications that were mentioned on different social media platforms, focussing on their differences and similarities with citation counts. Design/methodology/approach - Social media metrics and readership counts, associated with 500,216 publications and their citation data from the Web of Science database, were collected from Altmetric.com and Mendeley. Results are presented through descriptive statistical analyses together with science maps generated with VOSviewer. Findings - The results confirm Mendeley as the most prevalent social media source with similar characteristics to citations in their distribution across fields and their density in average values per publication. The humanities, natural sciences, and engineering disciplines have a much lower presence of social media metrics. Twitter has a stronger focus on general medicine and social sciences. Other sources (blog, Facebook, Google+, and news media mentions) are more prominent in regards to multidisciplinary journals. Originality/value - This paper reinforces the relevance of Mendeley as a social media source for analytical purposes from a disciplinary perspective, being particularly relevant for the social sciences (together with Twitter). Key implications for the use of social media metrics on the evaluation of research performance (e.g. the concentration of some social media metrics, such as blogs, news items, etc., around multidisciplinary journals) are identified.

Date

20. 1.2015 18:30:22

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Abstract

Purpose The introduction of "altmetrics" as new tools to analyze scientific impact within the reward system of science has challenged the hegemony of citations as the predominant source for measuring scientific impact. Mendeley readership has been identified as one of the most important altmetric sources, with several features that are similar to citations. The purpose of this paper is to perform an in-depth analysis of the differences and similarities between the distributions of Mendeley readership and citations across fields. Design/methodology/approach The authors analyze two issues by using in each case a common analytical framework for both metrics: the shape of the distributions of readership and citations, and the field normalization problem generated by differences in citation and readership practices across fields. In the first issue the authors use the characteristic scores and scales method, and in the second the measurement framework introduced in Crespo et al. (2013). Findings There are three main results. First, the citations and Mendeley readership distributions exhibit a strikingly similar degree of skewness in all fields. Second, the results on "exchange rates (ERs)" for Mendeley readership empirically supports the possibility of comparing readership counts across fields, as well as the field normalization of readership distributions using ERs as normalization factors. Third, field normalization using field mean readerships as normalization factors leads to comparably good results. Originality/value These findings open up challenging new questions, particularly regarding the possibility of obtaining conflicting results from field normalized citation and Mendeley readership indicators; this suggests the need for better determining the role of the two metrics in capturing scientific recognition.

Date

20. 1.2015 18:30:22

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Abstract

The article presents three advanced citation-based methods used to detect potential breakthrough articles among very highly cited articles. We approach the detection of such articles from three different perspectives in order to provide different typologies of breakthrough articles. In all three cases we use the hierarchical classification of scientific publications developed at CWTS based on direct citation relationships. We assume that such contextualized articles focus on similar research interests. We utilize the characteristics scores and scales (CSS) approach to partition citation distributions and implement a specific filtering algorithm to sort out potential highly-cited "followers," articles not considered breakthroughs. After invoking thresholds and filtering, three methods are explored: A very exclusive one where only the highest cited article in a micro-cluster is considered as a potential breakthrough article (M1); as well as two conceptually different methods, one that detects potential breakthrough articles among the 2% highest cited articles according to CSS (M2a), and finally a more restrictive version where, in addition to the CSS 2% filter, knowledge diffusion is also considered (M2b). The advance citation-based methods are explored and evaluated using validated publication sets linked to different Danish funding instruments including centers of excellence.

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Abstract

An extensive analysis of the presence of different altmetric indicators provided by Altmetric.com across scientific fields is presented, particularly focusing on their relationship with citations. Our results confirm that the presence and density of social media altmetric counts are still very low and not very frequent among scientific publications, with 15%-24% of the publications presenting some altmetric activity and concentrated on the most recent publications, although their presence is increasing over time. Publications from the social sciences, humanities, and the medical and life sciences show the highest presence of altmetrics, indicating their potential value and interest for these fields. The analysis of the relationships between altmetrics and citations confirms previous claims of positive correlations but is relatively weak, thus supporting the idea that altmetrics do not reflect the same kind of impact as citations. Also, altmetric counts do not always present a better filtering of highly-cited publications than journal citation scores. Altmetric scores (particularly mentions in blogs) are able to identify highly-cited publications with higher levels of precision than journal citation scores (JCS), but they have a lower level of recall. The value of altmetrics as a complementary tool of citation analysis is highlighted, although more research is suggested to disentangle the potential meaning and value of altmetric indicators for research evaluation.

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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 study of the citation histories and ageing of documents are topics that have been addressed from several perspectives, especially in the analysis of documents with delayed recognition or sleeping beauties. However, there is no general methodology that can be extensively applied for different time periods or research fields. In this article, a new methodology for the general analysis of the ageing and durability of scientific papers is presented. This methodology classifies documents into three general types: delayed documents, which receive the main part of their citations later than normal documents; flashes in the pan, which receive citations immediately after their publication but are not cited in the long term; and normal documents, documents with a typical distribution of citations over time. These three types of durability have been analyzed considering the whole population of documents in the Web of Science with at least 5 external citations (i.e., not considering self-citations). Several patterns related to the three types of durability have been found and the potential for further research of the developed methodology is discussed.