An index to quantify an individual's scientific research output
15 Nov 2005-Proceedings of the National Academy of Sciences of the United States of America (National Academy of Sciences)-Vol. 102, Iss: 46, pp 16569-16572
TL;DR: The index h, defined as the number of papers with citation number ≥h, is proposed as a useful index to characterize the scientific output of a researcher.
Abstract: I propose the index h, defined as the number of papers with citation number ≥h, as a useful index to characterize the scientific output of a researcher.
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TL;DR: This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifies the evolution, applications, and emerging research areas of BI&A, and introduces and characterized the six articles that comprise this special issue in terms of the proposed BI &A research framework.
Abstract: Business intelligence and analytics (BI&A) has emerged as an important area of study for both practitioners and researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations. This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifies the evolution, applications, and emerging research areas of BI&A. BI&A 1.0, BI&A 2.0, and BI&A 3.0 are defined and described in terms of their key characteristics and capabilities. Current research in BI&A is analyzed and challenges and opportunities associated with BI&A research and education are identified. We also report a bibliometric study of critical BI&A publications, researchers, and research topics based on more than a decade of related academic and industry publications. Finally, the six articles that comprise this special issue are introduced and characterized in terms of the proposed BI&A research framework.
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TL;DR: This paper proposes a unique open-source tool, designed by the authors, called bibliometrix, for performing comprehensive science mapping analysis, programmed in R, and can be rapidly upgraded and integrated with other statistical R-packages.
Abstract: The use of bibliometrics is gradually extending to all disciplines. It is particularly suitable for science mapping at a time when the emphasis on empirical contributions is producing voluminous, fragmented, and controversial research streams. Science mapping is complex and unwieldly because it is multi-step and frequently requires numerous and diverse software tools, which are not all necessarily freeware. Although automated workflows that integrate these software tools into an organized data flow are emerging, in this paper we propose a unique open-source tool, designed by the authors, called bibliometrix, for performing comprehensive science mapping analysis. bibliometrix supports a recommended workflow to perform bibliometric analyses. As it is programmed in R, the proposed tool is flexible and can be rapidly upgraded and integrated with other statistical R-packages. It is therefore useful in a constantly changing science such as bibliometrics.
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TL;DR: It is shown that the g-index inherits all the good properties of the h-index and better takes into account the citation scores of the top articles and yields a better distinction between and order of the scientists from the point of view of visibility.
Abstract: The g-index is introduced as an improvement of the h-index of Hirsch to measure the global citation performance of a set of articles. If this set is ranked in decreasing order of the number of citations that they received, the g-index is the (unique) largest number such that the top g articles received (together) at least g 2 citations. We prove the unique existence of g for any set of articles and we have that g ≥ h. The general Lotkaian theory of the g-index is presented and we show that g = (α-1 / α-2) α-1/α T 1/α where a> 2 is the Lotkaian exponent and where T denotes the total number of sources. We then present the g-index of the (still active) Price medallists for their complete careers up to 1972 and compare it with the h-index. It is shown that the g-index inherits all the good properties of the h-index and, in addition, better takes into account the citation scores of the top articles. This yields a better distinction between and order of the scientists from the point of view of visibility.
1,812 citations
TL;DR: Zehn Grundsatze um Forschung zu bewerten, drangen Diana Hicks, Paul Wouters und Kollegen einiges zusammen wirkt.
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TL;DR: In this paper, the authors proposed the stretched exponential family as a complement to the often used power law distributions, which has many advantages, among which to be economical with only two adjustable parameters with clear physical interpretation.
Abstract: To account quantitatively for many reported “natural” fat tail distributions in Nature and Economy, we propose the stretched exponential family as a complement to the often used power law distributions. It has many advantages, among which to be economical with only two adjustable parameters with clear physical interpretation. Furthermore, it derives from a simple and generic mechanism in terms of multiplicative processes. We show that stretched exponentials describe very well the distributions of radio and light emissions from galaxies, of US GOM OCS oilfield reserve sizes, of World, US and French agglomeration sizes, of country population sizes, of daily Forex US-Mark and Franc-Mark price variations, of Vostok (near the south pole) temperature variations over the last 400 000 years, of the Raup-Sepkoski's kill curve and of citations of the most cited physicists in the world. We also discuss its potential for the distribution of earthquake sizes and fault displacements. We suggest physical interpretations of the parameters and provide a short toolkit of the statistical properties of the stretched exponentials. We also provide a comparison with other distributions, such as the shifted linear fractal, the log-normal and the recently introduced parabolic fractal distributions.
763 citations
TL;DR: The first extensive measurement of the occurrence of Sleeping Beauties in the science literature is reported, derived from the measurements an ‘awakening’ probability function and identified the ‘most extreme Sleeping Beauty so far’.
Abstract: A 'Sleeping Beauty in Science' is a publication that goes unnoticed ('sleeps') for a long time and then, almost suddenly, attracts a lot of attention ('is awakened by a prince'). We here report the -to our knowledge- first extensive measurement of the occurrence of Sleeping Beauties in the science literature. We derived from the measurements an 'awakening' probability function and identified the 'most extreme Sleeping Beauty so far'.
466 citations