Search (101 results, page 1 of 6)

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Abstract

I studied the factors (citations, self-citations, and number of articles) that influenced large changes in only 1 year in the impact factors (IFs) of journals. A set of 360 instances of journals with large increases or decreases in their IFs from a given year to the following was selected from journals in the Journal Citation Reports from 1998 to 2007 (40 journals each year). The main factor influencing large changes was the change in the number of citations. About 54% of the increases and 42% of the decreases in the journal IFs were associated with changes in the journal self-citations.

Date

22. 1.2011 12:53:00

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Date

28. 9.2010 12:54:22

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Abstract

I propose the use of h-plots for visualizing the asymmetric relationships between the citing and cited profiles of journals in a common map. With this exploratory tool, we can understand better the journal's dual roles of citing and being cited in a reference network. The h-plot is introduced and its use is validated with a set of 25 journals belonging to the statistics area. The relatedness factor is considered for describing the relations of citations from a journal "i" to a journal "j," and the citations from the journal "j" to the journal "i." More information has been extracted from the h-plot, compared with other statistical techniques for modelling and representing asymmetric data, such as multidimensional unfolding.

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Abstract

Using a very small sample of 8 data sets it was recently shown by De Visscher (2011) that the g-index is very close to the square root of the total number of citations. It was argued that there is no bibliometrically meaningful difference. Using another somewhat larger empirical sample of 26 data sets I show that the difference may be larger and I argue in favor of the g-index.

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Abstract

This paper provides a better understanding of the implications of researchers' social networks in bibliographic references. Using a set of chemistry papers and conducting interviews with their authors (n = 32), I characterize the type of relation the author has with the authors of the references contained in his/her paper (n = 3,623). I show that citation relationships do not always involve underlying personal exchanges and that unknown references are an essential component, revealing segmentations in scientific groups. The relationships implied by references are of various strengths and origins. Several inclusive social circles are then identified: co-authors, close acquaintances, colleagues, invisible colleges, peers, contactables, and strangers. I conclude that publication is a device that contributes to a relatively stable distribution among the various social circles that structure scientific sociability.

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Abstract

In this article I investigate the shortcomings of exact string match-based author self-citation detection methods. The contributions of this study are twofold. First, I apply a fuzzy string matching algorithm for self-citation detection and benchmark this approach and other common methods of exclusively author name-based self-citation detection against a manually curated ground truth sample. Near full recall can be achieved with the proposed method while incurring only negligible precision loss. Second, I report some important observations from the results about the extent of latent self-citations and their characteristics and give an example of the effect of improved self-citation detection on the document level self-citation rate of real data.

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Date

18. 3.2014 19:13:22

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Abstract

I studied the distribution of articles and citations in journals between 1998 and 2007 according to an empirical function with two exponents. These variables showed good fit to a beta function with two exponents.

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Abstract

The h-index was devised to represent a scholar's contributions to his field with respect to the number of publications and citations. It does not, however, take into consideration the scholar's position in the authorship list. I recommend a new supplementary index to score academics, representing the relative contribution to the papers with impact, be reported alongside the h-index. I call this index the AP-index, and it is simply defined as the average position in which an academic appears in authorship lists, on articles that factor in to that academic's h-index.

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Abstract

The variables investment, benefit, and yield were defined to study the influence of journal self-citations on the impact factor. Investment represents the share of journal self-citations that contribute to the impact factor. Benefit is defined as the ratio of journal impact factor including self-citations to journal impact factor without self-citations. Yield is the relationship between benefit and investment. I selected all journals included in 2008 in the Science Citation Index version of Journal Citation Reports. After deleting 482 records for reasons to be explained, I used a final set of 6,138 journals to study the distribution of the variables defined above. The distribution of benefit differed from the distribution of investment and yield. The top 20-ranked journals were not the same for all three variables. The yield of self-citations on the journal impact factor was, in general, very modest.

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Abstract

Using data from the Web of Science (WoS), we analyze the mutual information among university, industry, and government addresses (U-I-G) at the country level for a number of countries. The dynamic evolution of the Triple Helix can thus be compared among developed and developing nations in terms of cross-sectional coauthorship relations. The results show that the Triple Helix interactions among the three subsystems U-I-G become less intensive over time, but unequally for different countries. We suggest that globalization erodes local Triple Helix relations and thus can be expected to have increased differentiation in national systems since the mid-1990s. This effect of globalization is more pronounced in developed countries than in developing ones. In the dynamic analysis, we focus on a more detailed comparison between China and the United States. Specifically, the Chinese Academy of the (Social) Sciences is changing increasingly from a public research institute to an academic one, and this has a measurable effect on China's position in the globalization.

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Abstract

The use of research impact metrics and analytics has become an integral component to many aspects of institutional assessment. Many platforms currently exist to provide such analytics, both proprietary and open source; however, the functionality of these systems may not always overlap to serve uniquely specific needs. In this paper, I describe a novel web-based platform, named Manifold, that I built to serve custom research impact assessment needs in the University of Minnesota Medical School. Built on a standard LAMP architecture, Manifold automatically pulls publication data for faculty from Scopus through APIs, calculates impact metrics through automated analytics, and dynamically generates report-like profiles that visualize those metrics. Work on this project has resulted in many lessons learned about challenges to sustainability and scalability in developing a system of such magnitude.

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Abstract

The approach based on "thermodynamic" considerations that can quantify research performance using an exergy term defined as X = iC, where i is the impact and C is the number of citations is now extended to cases where fractionalized counting of citations is used instead of integer counting.

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Abstract

I propose the index $\hbar$ ("hbar"), defined as the number of papers of an individual that have citation count larger than or equal to the $\hbar$ of all coauthors of each paper, as a useful index to characterize the scientific output of a researcher that takes into account the effect of multiple authorship. The bar is higher for $\hbar.$

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Abstract

The h-index has been shown to increase in many cases mostly because of citations to rather old publications. This inertia can be circumvented by restricting the evaluation to a citation time window. Here I report results of an empirical study analyzing the evolution of the thus defined timed h-index in dependence on the length of the citation time window.

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Abstract

I discuss how, given a certain number of articles and citations of these articles, the h-index and the g-index are affected by the level of concentration of the citations. This offers the opportunity for a comparison between these 2 indices from a new perspective.

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Content

Vgl.: https://www.b-i-t-online.de/heft/2017-03-index.php.

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Abstract

Based on the principles of the h-index, I propose a new measure, the w-index, as a particularly simple and more useful way to assess the substantial impact of a researcher's work, especially regarding excellent papers. The w-index can be defined as follows: If w of a researcher's papers have at least 10w citations each and the other papers have fewer than 10(w+1) citations, that researcher's w-index is w. The results demonstrate that there are noticeable differences between the w-index and the h-index, because the w-index plays close attention to the more widely cited papers. These discrepancies can be measured by comparing the ranks of 20 astrophysicists, a few famous physical scientists, and 16 Price medalists. Furthermore, I put forward the w(q)-index to improve the discriminatory power of the w-index and to rank scientists with the same w. The factor q is the least number of citations a researcher with w needed to reach w+1. In terms of both simplicity and accuracy, the w-index or w(q)-index can be widely used for evaluation of scientists, journals, conferences, scientific topics, research institutions, and so on.

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Abstract

Bibliometric evaluations of research outputs in the social sciences and humanities are challenging due to limitations associated with Web of Science data; however, background literature has shown that scholars are interested in stimulating improvements. We give special attention to book reviews processed by Web of Sciencehistory and literature journals, focusing on two types: Type I (i.e., reference to book only) and Type II (i.e., reference to book and other scholarly sources). Bibliometric data are collected and analyzed for a large set of reviews (1981-2009) to observe general publication patterns and patterns of citedness and co-citedness with books under review. Results show that reviews giving reference only to the book (Type I) are published more frequently while reviews referencing the book and other works (Type II) are more likely to be cited. The referencing culture of the humanities makes it difficult to understand patterns of co-citedness between books and review articles without further in-depth content analyses. Overall, citation counts to book reviews are typically low, but our data showed that they are scholarly and do play a role in the scholarly communication system. In the disciplines of history and literature, where book reviews are prominent, counting the number and type of reviews that a scholar produces throughout his/her career is a positive step forward in research evaluations. We propose a new set of journal quality indicators for the purpose of monitoring their scholarly influence.