Search (556 results, page 1 of 28)

  • × theme_ss:"Informetrie"
  1. Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014) 0.10
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    Date
    18. 3.2014 19:13:22
  2. Su, Y.; Han, L.-F.: ¬A new literature growth model : variable exponential growth law of literature (1998) 0.10
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    Date
    22. 5.1999 19:22:35
  3. Chung, Y.-K.: Bradford distribution and core authors in classification systems literature (1994) 0.08
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    Abstract
    Bradford's law of scatter was applied to the analysis of the authors of source documents on the subject of classification schemes, published in core periodicals over the period 1981-1990. Results indicated that: core authors of the international classification system literature are Library of Congress, M. Dewey, S. Ranganathan, J. Comaroni, A. Neelameghan, L. Chan and K. Markey; the highly cited authors are linked either to the developers of the classification schemes or to a research centre, or else they authored the most frequently cited books; and the data conforms to Bradford's Law of Scatter
  4. Bauer, J.; Leydesdorff, L.; Bornmann, L.: Highly cited papers in Library and Information Science (LIS) : authors, institutions, and network structures (2016) 0.07
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    Abstract
    As a follow-up to the highly cited authors list published by Thomson Reuters in June 2014, we analyzed the top 1% most frequently cited papers published between 2002 and 2012 included in the Web of Science (WoS) subject category "Information Science & Library Science." In all, 798 authors contributed to 305 top 1% publications; these authors were employed at 275 institutions. The authors at Harvard University contributed the largest number of papers, when the addresses are whole-number counted. However, Leiden University leads the ranking if fractional counting is used. Twenty-three of the 798 authors were also listed as most highly cited authors by Thomson Reuters in June 2014 (http://highlycited.com/). Twelve of these 23 authors were involved in publishing 4 or more of the 305 papers under study. Analysis of coauthorship relations among the 798 highly cited scientists shows that coauthorships are based on common interests in a specific topic. Three topics were important between 2002 and 2012: (a) collection and exploitation of information in clinical practices; (b) use of the Internet in public communication and commerce; and (c) scientometrics.
  5. Egghe, L.; Ravichandra Rao, I.K.: Study of different h-indices for groups of authors (2008) 0.07
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    Abstract
    In this article, for any group of authors, we define three different h-indices. First, there is the successive h-index h2 based on the ranked list of authors and their h-indices h1 as defined by Schubert (2007). Next, there is the h-index hP based on the ranked list of authors and their number of publications. Finally, there is the h-index hC based on the ranked list of authors and their number of citations. We present formulae for these three indices in Lotkaian informetrics from which it also follows that h2 < hp < hc. We give a concrete example of a group of 167 authors on the topic optical flow estimation. Besides these three h-indices, we also calculate the two-by-two Spearman rank correlation coefficient and prove that these rankings are significantly related.
  6. Siddiqui, M.A.: ¬A bibliometric study of authorship characteristics in four international information science journals (1997) 0.07
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    Abstract
    Reports results of a bibliometric study of the authorship characteristics of articles published in 4 major information science periodicals: JASIS, Information technology and libraries, Journal of information science, and Program. The aim was to determine the details of their authors, such as: sex, occupation, affiliation, geographic distribution, and institutional affiliation. A total of 163 articles published in 1993 and written by 294 authors were analyzed. Results indicate that: men (206 or 70%) publish 3.0 times more articles than women (69 or 23,5%). Schools of library and information science contributed the most authors. The majority of authors came from the USA (148 or 50,3%), with the Midwest region claiming the largest share (110 or 25,0%). Academic libraries (110 or 37,4%) account for the major share of library publication. 12 schools of library and information science, in the USA, contributed 32 authors (50,0%) and assistant professors (25 or 39,1%) publish the most in these library schools. Male school of library and information science authors publish 1,6 times more than their female counterparts
    Source
    International forum on information and documentation. 22(1997) no.3, S.3-23
  7. Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014) 0.06
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    Date
    22. 8.2014 17:05:18
  8. Leydesdorff, L.: Theories of citation? (1999) 0.06
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    Abstract
    Citations support the communication of specialist knowledge by allowing authors and readers to make specific selections in several contexts at the same time. In the interactions between the social network of authors and the network of their reflexive communications, a sub textual code of communication with a distributed character has emerged. Citation analysis reflects on citation practices. Reference lists are aggregated in scientometric analysis using one of the available contexts to reduce the complexity: geometrical representations of dynamic operations are reflected in corresponding theories of citation. The specific contexts represented in the modern citation can be deconstructed from the perspective of the cultural evolution of scientific communication
  9. Zhang, L.; Thijs, B.; Glänzel, W.: What does scientometrics share with other "metrics" sciences? (2013) 0.06
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    Abstract
    In this article, the authors answer the question of whether the field of scientometrics/bibliometrics shares essential characteristics of "metrics" sciences. To achieve this objective, the citation network of seven selected metrics and their information environment is analyzed.
  10. Castanha, R.C.G.; Wolfram, D.: ¬The domain of knowledge organization : a bibliometric analysis of prolific authors and their intellectual space (2018) 0.06
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    Abstract
    The domain of knowledge organization (KO) represents a foundational area of information science. One way to better understand the intellectual structure of the KO domain is to apply bibliometric methods to key contributors to the literature. This study analyzes the most prolific contributing authors to the journal Knowledge Organization, the sources they cite and the citations they receive for the period 1993 to 2016. The analyses were conducted using visualization outcomes of citation, co-citation and author bibliographic coupling analysis to reveal theoretical points of reference among authors and the most prominent research themes that constitute this scientific community. Birger Hjørland was the most cited author, and was situated at or near the middle of each of the maps based on different citation relationships. The proximities between authors resulting from the different citation relationships demonstrate how authors situate themselves intellectually through the citations they give and how other authors situate them through the citations received. There is a consistent core of theoretical references as well among the most productive authors. We observed a close network of scholarly communication between the authors cited in this core, which indicates the actual role of the journal Knowledge Organization as a space for knowledge construction in the area of knowledge organization.
    Source
    Knowledge organization. 45(2018) no.1, S.13-22
  11. Leydesdorff, L.; Bornmann, L.; Wagner, C.S.: ¬The relative influences of government funding and international collaboration on citation impact (2019) 0.06
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    Date
    8. 1.2019 18:22:45
  12. Egghe, L.; Rousseau, R.; Hooydonk, G. van: Methods for accrediting publications to authors or countries : consequences for evaluation studies (2000) 0.06
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    Abstract
    One aim of science evaluation studies is to determine quantitatively the contribution of different players (authors, departments, countries) to the whole system. This information is then used to study the evolution of the system, for instance to gauge the results of special national or international programs. Taking articles as our basic data, we want to determine the exact relative contribution of each coauthor or each country. These numbers are brought together to obtain country scores, or department scores, etc. It turns out, as we will show in this article, that different scoring methods can yield totally different rankings. Conseqeuntly, a ranking between countries, universities, research groups or authors, based on one particular accrediting methods does not contain an absolute truth about their relative importance
  13. Egghe, L.; Ravichandra Rao, I.K.: Duality revisited : construction of fractional frequency distributions based on two dual Lotka laws (2002) 0.06
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    Abstract
    Fractional frequency distributions of, for example, authors with a certain (fractional) number of papers are very irregular and, therefore, not easy to model or to explain. This article gives a first attempt to this by assuming two simple Lotka laws (with exponent 2): one for the number of authors with n papers (total count here) and one for the number of papers with n authors, n E N. Based an an earlier made convolution model of Egghe, interpreted and reworked now for discrete scores, we are able to produce theoretical fractional frequency distributions with only one parameter, which are in very close agreement with the practical ones as found in a large dataset produced earlier by Rao. The article also shows that (irregular) fractional frequency distributions are a consequence of Lotka's law, and are not examples of breakdowns of this famous historical law.
  14. Egghe, L.: ¬A model for the size-frequency function of coauthor pairs (2008) 0.06
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    Abstract
    Lotka's law was formulated to describe the number of authors with a certain number of publications. Empirical results (Morris & Goldstein, 2007) indicate that Lotka's law is also valid if one counts the number of publications of coauthor pairs. This article gives a simple model proving this to be true, with the same Lotka exponent, if the number of coauthored papers is proportional to the number of papers of the individual coauthors. Under the assumption that this number of coauthored papers is more than proportional to the number of papers of the individual authors (to be explained in the article), we can prove that the size-frequency function of coauthor pairs is Lotkaian with an exponent that is higher than that of the Lotka function of individual authors, a fact that is confirmed in experimental results.
  15. Milard, B.; Tanguy, L.: Citations in scientific texts : do social relations matter? (2018) 0.06
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    Abstract
    This article presents an investigation of the role of social relations in the writing of scientific articles through the study of in-text citations. Does the fact that the author of an article knows the author whose work he or she cites have an impact on the context of the citation? Because citations are commonly used as criteria for research evaluation, it is important to question their social background to better understand how it impacts textual features. We studied a collection of science articles (N?=?123) from 5 disciplines and interviewed their authors (N?=?84) to: (a) identify the social relations between citing and cited authors; and (b) measure the correlation between a set of features related to in-text citations (N?=?6,956) and the identified social relations. Our pioneering work, mixing sociological and linguistic results, shows that social relations between authors can partly explain the variations of citations in terms of frequency, position and textual context.
  16. Bornmann, L.; Leydesdorff, L.: Which cities produce more excellent papers than can be expected? : a new mapping approach, using Google Maps, based on statistical significance testing (2011) 0.06
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    Abstract
    The methods presented in this paper allow for a statistical analysis revealing centers of excellence around the world using programs that are freely available. Based on Web of Science data (a fee-based database), field-specific excellence can be identified in cities where highly cited papers were published more frequently than can be expected. Compared to the mapping approaches published hitherto, our approach is more analytically oriented by allowing the assessment of an observed number of excellent papers for a city against the expected number. Top performers in output are cities in which authors are located who publish a statistically significant higher number of highly cited papers than can be expected for these cities. As sample data for physics, chemistry, and psychology show, these cities do not necessarily have a high output of highly cited papers.
  17. Avramescu, A.: Teoria difuziei informatiei stiintifice (1997) 0.05
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    Abstract
    The theory of diffusion can be successfully applied to scientific information dissemination by identifying space with a series of successive authors, and potential (temperature) with the interest of new authors towards earlier published papers, measured by the number of citations. As the total number of citation equals the number of references, the conservation law is fulfilled and Fourier's parabolic differential equation can be applied
    Date
    22. 2.1999 16:16:11
  18. Brody, T.; Harnad, S.; Carr, L.: Earlier Web usage statistics as predictors of later citation impact (2006) 0.05
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    Abstract
    The use of citation counts to assess the impact of research articles is well established. However, the citation impact of an article can only be measured several years after it has been published. As research articles are increasingly accessed through the Web, the number of times an article is downloaded can be instantly recorded and counted. One would expect the number of times an article is read to be related both to the number of times it is cited and to how old the article is. The authors analyze how short-term Web usage impact predicts medium-term citation impact. The physics e-print archive-arXiv.org-is used to test this.
  19. Eck, N.J. van; Waltman, L.: Appropriate similarity measures for author co-citation analysis (2008) 0.05
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    Abstract
    We provide in this article a number of new insights into the methodological discussion about author co-citation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors' co-citation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. We show by means of an example that the choice of an appropriate similarity measure has a high practical relevance. Finally, we discuss the use of similarity measures for statistical inference.
  20. Zhu, Y.; Quan, L.; Chen, P.-Y.; Kim, M.C.; Che, C.: Predicting coauthorship using bibliographic network embedding (2023) 0.05
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    Abstract
    Coauthorship prediction applies predictive analytics to bibliographic data to predict authors who are highly likely to be coauthors. In this study, we propose an approach for coauthorship prediction based on bibliographic network embedding through a graph-based bibliographic data model that can be used to model common bibliographic data, including papers, terms, sources, authors, departments, research interests, universities, and countries. A real-world dataset released by AMiner that includes more than 2 million papers, 8 million citations, and 1.7 million authors were integrated into a large bibliographic network using the proposed bibliographic data model. Translation-based methods were applied to the entities and relationships to generate their low-dimensional embeddings while preserving their connectivity information in the original bibliographic network. We applied machine learning algorithms to embeddings that represent the coauthorship relationships of the two authors and achieved high prediction results. The reference model, which is the combination of a network embedding size of 100, the most basic translation-based method, and a gradient boosting method achieved an F1 score of 0.9 and even higher scores are obtainable with different embedding sizes and more advanced embedding methods. Thus, the strengths of the proposed approach lie in its customizable components under a unified framework.

Years

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