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- Author or Editor: Wolfgang Glänzel x
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Abstract
With the modern technology fast developing, most of entities can be observed by different perspectives. These multiple view information allows us to find a better pattern as long as we integrate them in an appropriate way. So clustering by integrating multi-view representations that describe the same class of entities has become a crucial issue for knowledge discovering. We integrate multi-view data by a tensor model and present a hybrid clustering method based on Tucker-2 model, which can be regarded as an extension of spectral clustering. We apply our hybrid clustering method to scientific publication analysis by integrating citation-link and lexical content. Clustering experiments are conducted on a large-scale journal set retrieved from the Web of Science (WoS) database. Several relevant hybrid clustering methods are cross compared with our method. The analysis of clustering results demonstrate the effectiveness of the proposed algorithm. Furthermore, we provide a cognitive analysis of the clustering results as well as the visualization as a mapping of the journal set.
Abstract
Based on data from the Science Citation Index Expanded (SCIE) and using scientometric methods, we conducted a systematic analysis of Chinese regional contributions and international collaboration in terms of scientific publications, publication activity, and citation impact. We found that regional contributions are highly skewed. The top positions measured by number of publications or citations, share of publications or citations are taken by almost the same set of regions. But this is not the case when indicators for relative citation impact are used. Comparison between regional scientific output and R&D expenditure shows that Spearman’s rank correlation coefficient between the two indicators is rather low among the leading publication regions.
Abstract
Recent studies have reported on a steady decline of Sweden's relative citation impact in almost all science fields, above all in the life sciences. The authors attempt to shed light on the observed decline in Swedish neuroscience through a detailed citation analysis at different level of aggregations. Thus national citation data are decomposed to the institutional, departmental and individual level. Both, the decomposition of national science indicators and changing collaboration patterns in Swedish neuroscience reveal interesting details on the 'anatomy' of a decline.
The discussion about how to treat author self-citations driven by policy application and quality measurement intensified in the last years. The definition introduced by Snyder and Bonzi has - in lack of any reasonable alternative - been used in bibliometric practice for science policy purposes. This method, however, does not take into account the weight of self-citing authors among co-authors of both the cited and citing papers. The objective of the present paper is to quantify the weight of self-citations with respect to co-authorship. The analysis is conducted at two levels: at the macro level, namely, for fifteen subject fields and the most active forty countries, and at the meso level, for a set of selected research institutions.
Summary In the present study full-text analysis and traditional bibliometric methods are combined to improve the efficiency of the individual methods in the mapping of science. The methodology is applied to map research papers from a special issue of Scientometrics. The outcomes substantiate that such hybrid methodology can be applied to both research evaluation and information retrieval. The subject classification given by the guest-editors of the special issue is used for validation purposes. Because of the limited number of papers underlying the study the paper is considered a pilot study that will be extended in a later study on the basis of a larger corpus.
Abstract
According to Garfield (1980),most scientists can name an example of an important discovery that had little initial impact on contemporary research. And he uses Mendel's work a classical example. Delayed recognition is sometimes used by scientists as an argument against citation-based indicators based on citation windows defined for a short- or medium-term initial period beginning with the paper's publication year. This study is focussed on a large-scale analysis of the citation history of all papers indexed in the 1980 annual volume of the Science Citation Index. The objective is two-fold, particularly, to analyse whether the share of delayed recognition papers is significant and whether such papers are typical of the work of their authors at that time. In a first step, the background of advanced bibliometric models by Glnzel, Egghe, Rousseau and Burrell of stochastic citation processes and first-citation distributions is described briefly. The second part is devoted to the bibliometric analysis of first-citation statistics and of the phenomenon of citation delay. In a third step, finally, delayed reception publications have been studied individually. Their topics and the citation patterns of other papers by the same authors have been studied to uncover principles of regularity or exceptionality of delayed reception publications.
Abstract
Previous studies have shown that hybrid clustering methods that incorporate textual content and bibliometric information can outperform clustering methods that use only one of these components. In this paper we apply a hybrid clustering method based on Fisher’s inverse chisquare to integrate full-text with citations and to provide a mapping of the field of information science. We quantitatively and qualitatively asses the added value of such an integrated analysis and we investigate whether the clustering outcome is a better representation of the field by comparing with a text-only clustering and with another hybrid method based on linear combination of distance matrices. Our data set consists of almost 1000 articles and notes published in the period 2002–2004 in 5 representative journals. The optimal number of clusters for the field is 5, determined by using a combination of distance-based and stability-based methods. Term networks present the cognitive structure of the field and are complemented by the most representative publications. Three large traditional sub-disciplines, particularly, information retrieval, bibliometrics/scientometrics, and more social aspects, and two smaller clusters about patent analysis and webometrics, can be distinguished.
Summary
In the present paper, the evolution of publication activity and citation impact in Brazil is studied for the period 1991-2003. Besides the analysis of trends in publication and citation patterns and of national publication profiles, an attempt is made to find statistical evidences of the relation between international co-authorship and both research profile and citation impact in the Latin American region. Despite similarities and strong co-publication links with the other countries in the region, Brazil has nonetheless a specific research profile, and forms the largest potential in the region.
Abstract
Previous studies have shown that hybrid clustering methods based on textual and citation information outperforms clustering methods that use only one of these components. However, former methods focus on the vector space model. In this paper we apply a hybrid clustering method which is based on the graph model to map the Web of Science database in the mirror of the journals covered by the database. Compared with former hybrid clustering strategies, our method is very fast and even achieves better clustering accuracy. In addition, it detects the number of clusters automatically and provides a top-down hierarchical analysis, which fits in with the practical application. We quantitatively and qualitatively asses the added value of such an integrated analysis and we investigate whether the clustering outcome provides an appropriate representation of the field structure by comparing with a text-only or citation-only clustering and with another hybrid method based on linear combination of distance matrices. Our dataset consists of about 8,000 journals published in the period 2002–2006. The cognitive analysis, including the ranked journals, term annotation and the visualization of cluster structure demonstrates the efficiency of our strategy.
