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Wilmington, DE, United States

Publications that are not indexed by citation indices such as Web of Science (WoS) or Scopus are called “non-source items”. These have so far been neglected by most bibliometric analyses. The central issue of this study is to investigate the characteristics of non-source items and the effect of their inclusion in bibliometric evaluations in the social sciences, specifically German political science publications. The results of this study show that non-source items significantly increase the number of publications (+1,350 %) and to a lesser extent the number of citations from SCIE, SSCI, and A&HCI (+150 %) for evaluated political scientists. 42 % of non-source items are published as book chapters.Edited books and books are cited the most among non-source items. About 40 % of non-source items are in English, while 80 % of source items are in English. The citation rates of researchers taking non-source items into account are lower than those from source items, partially as a result of the limited coverage of WoS. In contrast, the H-indices of researchers taking only non-source items into account are higher than those from source items. In short, the results of this study show that non-source items should be included in bibliometric evaluations, regardless of their impact or the citations from them. The demand for a more comprehensive coverage of bibliometric database in the social sciences for a higher quality of evaluations is shown. © 2014, Akadémiai Kiadó, Budapest, Hungary. Source


Ye F.Y.,Zhejiang University | Ye F.Y.,Information Assurance
Journal of the American Society for Information Science and Technology | Year: 2011

Among existing theoretical models for the h-index, Hirsch's original approach, the Egghe-Rousseau model, and the Glänzel-Schubert model are the three main representatives. Assuming a power-law relation or Heaps' law between publications and citations a unified theoretical explanation for these three models is provided. It is shown that on the level of universities, the Glänzel-Schubert model fits best. © 2010 ASIS&T. Source


Larsen P.O.,Marievej 10A | von Ins M.,Information Assurance
Scientometrics | Year: 2010

The growth rate of scientific publication has been studied from 1907 to 2007 using available data from a number of literature databases, including Science Citation Index (SCI) and Social Sciences Citation Index (SSCI). Traditional scientific publishing, that is publication in peer-reviewed journals, is still increasing although there are big differences between fields. There are no indications that the growth rate has decreased in the last 50 years. At the same time publication using new channels, for example conference proceedings, open archives and home pages, is growing fast. The growth rate for SCI up to 2007 is smaller than for comparable databases. This means that SCI was covering a decreasing part of the traditional scientific literature. There are also clear indications that the coverage by SCI is especially low in some of the scientific areas with the highest growth rate, including computer science and engineering sciences. The role of conference proceedings, open access archives and publications published on the net is increasing, especially in scientific fields with high growth rates, but this has only partially been reflected in the databases. The new publication channels challenge the use of the big databases in measurements of scientific productivity or output and of the growth rate of science. Because of the declining coverage and this challenge it is problematic that SCI has been used and is used as the dominant source for science indicators based on publication and citation numbers. The limited data available for social sciences show that the growth rate in SSCI was remarkably low and indicate that the coverage by SSCI was declining over time. National Science Indicators from Thomson Reuters is based solely on SCI, SSCI and Arts and Humanities Citation Index (AHCI). Therefore the declining coverage of the citation databases problematizes the use of this source. © 2010 The Author(s). Source


Biesenbender S.,Information Assurance | Tosun J.,University of Heidelberg
Global Environmental Change | Year: 2014

What happens to policy innovations after they have been adopted? What factors account for subsequent changes to these policies? These are the research questions guiding this study on the spread of and subsequent changes to limit values for nitrogen oxide emissions from large combustion plants. By comparing the processes of diffusion and follow-up policy changes, we assess whether and how policy innovations translate into policy making. In so doing, we build on the literature on the determinants of policy diffusion and transfer. We employ original data on instances of policy adoption and policy change in 24 Organisation for Economic Co-operation and Development (OECD) countries over a period of thirty years (1976-2005). The data are analysed using semi-parametric event-history models. Our empirical findings show that both international and domestic factors account for the observed variation in our data regarding both first-time adoptions and post-adoption modifications. The results reveal that the subsequent tightening of emission standards faces greater obstacles than their mere diffusion (i.e., policy adoption). While international factors and supranational integration appear to impede the subsequent tightening of existing policies, international peer pressure is a strong predictor of an on-going regulatory commitment. Overall, adoption and accommodation processes seem to follow distinctive patterns, suggesting that a promising strategy in policy innovation research would involve differentiation between the first-time adoption and subsequent modification of policies. © 2014 Elsevier Ltd. Source


Wang J.,Georgia Institute of Technology | Wang J.,Catholic University of Leuven | Wang J.,Information Assurance
Journal of Informetrics | Year: 2014

One problem confronting the use of citation-based metrics in science studies and research evaluations is the Matthew effect. This paper reviews the role of citations in science and decomposes the Matthew effect in citations into three components: networking, prestige, and appropriateness. The networking and prestige effects challenge the validity of citation-based metrics, but the appropriateness effect does not. Using panel data of 1279 solo-authored papers' citation histories and fixed effects models, we test these three effects controlling for unobserved paper characteristics. We find no evidence of retroactive networking effect and only weak evidence of prestige effect (very small and not always significant), which provides some support for the use of citation-based metrics in science studies and evaluation practices. In addition, adding the appropriateness effect reduces the size of the prestige effect considerably, suggesting that previous studies controlling for paper quality but not appropriateness may have overestimated the prestige effect. © 2014 Elsevier Ltd. Source

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