Search (7 results, page 1 of 1)

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Abstract

In this article we present an empirical approach to the study of the statistical properties of bibliometric indicators on a very relevant but not simply available aggregation level: the research group. We focus on the distribution functions of a coherent set of indicators that are used frequently in the analysis of research performance. In this sense, the coherent set of indicators acts as a measuring instrument. Better insight into the statistical properties of a measuring instrument is necessary to enable assessment of the instrument itself. The most basic distribution in bibliometric analysis is the distribution of citations over publications, and this distribution is very skewed. Nevertheless, we clearly observe the working of the central limit theorem and find that at the level of research groups the distribution functions of the main indicators, particularly the journal- normalized and the field-normalized indicators, approach normal distributions. The results of our study underline the importance of the idea of group oeuvre, that is, the role of sets of related publications as a unit of analysis.

Date

22. 7.2006 16:20:22

Type

a

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Abstract

A representation of science as a citation density landscape is proposed and scaling rules with the field-specific citation density as a main topological property are investigated. The focus is on the size-dependence of several main bibliometric indicators for a large set of research groups while distinguishing between top-performance and lower-performance groups. It is demonstrated that this representation of the science system is particularly effective to understand the role and the interdependencies of the different bibliometric indicators and related topological properties of the landscape.

Date

22. 3.2009 19:03:12

Type

a

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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

Type

a

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Abstract

The statistical properties of bibliometric indicators related to research performance, field citation density, and journal impact were studied for the 100 largest European research universities. A size-dependent cumulative advantage was found for the impact of universities in terms of total number of citations. In the author's previous work, a similar scaling rule was found at the level of research groups. Therefore, this scaling rule is conjectured to be a prevalent property of the science system. The lower performance universities have a larger size-dependent cumulative advantage for receiving citations than top performance universities. For the lower performance universities, the fraction of noncited publications decreases considerably with size. Generally, the higher the average journal impact of the publications of a university, the lower the number of noncited publications. The average research performance was found not to dilute with size. Evidently, large universities, particularly top performance universities are characterized by being big and beautiful. They succeed in keeping a high performance over a broad range of activities. This most probably is an indication of their overall attractive scientific and intellectual power. It was also found that particularly for the lower performance universities, the field citation density provides a strong cumulative advantage in citations per publication. The relation between number of citations and field citation density found in this study can be considered as a second basic scaling rule of the science system. Top performance universities publish in journals with significantly higher journal impact as compared to the lower performance universities. A significant decrease of the fraction of self-citations with increasing research performance, average field citation density, and average journal impact was found.

Type

a

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Abstract

Previous research has demonstrated that lower performance groups have a larger size-dependent cumulative advantage for receiving citations than do top-performance groups. Furthermore, regardless of performance, larger groups have less not-cited publications. Particularly for the lower performance groups, the fraction of not-cited publications decreases considerably with size. These phenomena can be explained with a model in which self-citation acts as a promotion mechanism for external citations. In this article, we show that for self-citations, similar size-dependent scaling rules apply as for citations, but generally the power law exponents are higher for self-citations as compared to citations. We also find that the fraction of self-citations is smaller for the higher performance groups, and this fraction decreases more rapidly with increasing journal impact than that for lower performance groups. An interesting novel finding is that the variance in the correlation of the number of self-citations with size is considerably less than the variance for external citations. This is a clear indication that size is a stronger determinant for self-citations than it is for external citations. Both higher and particularly lower performance groups have a size-dependent cumulative advantage for self-citations, but for the higher performance groups only in the lower impact journals and in fields with low citation density.

Type

a

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Abstract

In this article we distinguish between top-performance and lower-performance groups in the analysis of statistical properties of bibliometric characteristics of two large sets of research groups. We find intriguing differences between top-performance and lower-performance groups, and between the two sets of research groups. These latter differences may indicate the influence of research management strategies. We report the following two main observations: First, lower-performance groups have a larger size-dependent cumulative advantage for receiving citations than top-performance groups. Second, regardless of performance, larger groups have fewer not-cited publications. Particularly for the lower-performance groups, the fraction of not-cited publications decreases considerably with size. We introduce a simple model in which processes at the microlevel lead to the observed phenomena at the macrolevel. Next, we fit our findings into the novel concept of hierarchically layered networks. In this concept, which provides the infrastructure for the model, a network of research groups constitutes a layer of one hierarchical step higher than the basic network of publications connected by citations. The cumulative size advantage of citations received by a group resembles preferential attachment in the basic network in which highly connected nodes (publications) increase their connectivity faster than less connected nodes. But in our study it is size that causes an advantage. In general, the larger a group (node in the research group network), the more incoming links this group acquires in a nonlinear, cumulative way. Nevertheless, top-performance groups are about an order of magnitude more efficient in creating linkages (i.e., receiving citations) than lower-performance groups. This implies that together with the size-dependent mechanism, preferential attachment, a quite common characteristic of complex networks, also works. Finally, in the framework of this study on performance-related differences of bibliometric properties of research groups, we also find that top-performance groups are, on average, more successful in the entire range of journal impact.

Type

a

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Abstract

This paper addresses a bibliometric methodology to discover the structure of the scientific 'landscape' in order to gain detailed insight into the development of MD fields, their interaction, and the transfer of knowledge between them. This methodology is appropriate to visualize the position of MD activities in relation to interdisciplinary MD developments, and particularly in relation to socio-economic problems. Furthermore, it allows the identification of the major actors. It even provides the possibility of foresight. We describe a first approach to apply bibliometric mapping as an instrument to investigate characteristics of knowledge transfer. In this paper we discuss the creation of 'maps of science' with help of advanced bibliometric methods. This 'bibliometric cartography' can be seen as a specific type of data-mining, applied to large amounts of scientific publications. As an example we describe the mapping of the field neuroscience, one of the largest and fast growing fields in the life sciences. The number of publications covered by this database is about 80,000 per year, the period covered is 1995-1998. Current research is going an to update the mapping for the years 1999-2002. This paper addresses the main lines of the methodology and its application in the study of knowledge transfer.

Source

Gaining insight from research information (CRIS2002): Proceedings of the 6th International Conference an Current Research Information Systems, University of Kassel, August 29 - 31, 2002. Eds: W. Adamczak u. A. Nase

Type

a