-
Bookstein, A.: Informetric distributions : I. Unified overview (1990)
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- Date
- 22. 7.2006 18:55:29
-
Bookstein, A.: Informetric distributions : II. Resilience to ambiguity (1990)
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- Date
- 22. 7.2006 18:55:55
-
Burrell, Q.L.: "Type/Token-Taken" informetrics : Some comments and further examples (2003)
0.02
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- Abstract
- Egghe has propounded the notion of Type/Token-Taken (T/TT) informetrics. In this note we show how his ideas relate to ones that are already well known in informetrics and resolve some of the specific problems posed.
-
Egghe, L.; Ravichandra Rao, I.K.: ¬The influence of the broadness of a query of a topic on its h-index : models and examples of the h-index of n-grams (2008)
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- Abstract
- The article studies the influence of the query formulation of a topic on its h-index. In order to generate pure random sets of documents, we used N-grams (N variable) to measure this influence: strings of zeros, truncated at the end. The used databases are WoS and Scopus. The formula h=T**1/alpha, proved in Egghe and Rousseau (2006) where T is the number of retrieved documents and is Lotka's exponent, is confirmed being a concavely increasing function of T. We also give a formula for the relation between h and N the length of the N-gram: h=D10**(-N/alpha) where D is a constant, a convexly decreasing function, which is found in our experiments. Nonlinear regression on h=T**1/alpha gives an estimation of , which can then be used to estimate the h-index of the entire database (Web of Science [WoS] and Scopus): h=S**1/alpha, , where S is the total number of documents in the database.
-
Egghe, L.; Rousseau, R.: ¬The Hirsch index of a shifted Lotka function and its relation with the impact factor (2012)
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- Abstract
- Based on earlier results about the shifted Lotka function, we prove an implicit functional relation between the Hirsch index (h-index) and the total number of sources (T). It is shown that the corresponding function, h(T), is concavely increasing. Next, we construct an implicit relation between the h-index and the impact factor IF (an average number of items per source). The corresponding function h(IF) is increasing and we show that if the parameter C in the numerator of the shifted Lotka function is high, then the relation between the h-index and the impact factor is almost linear.
-
Lewison, G.: ¬The work of the Bibliometrics Research Group (City University) and associates (2005)
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- Date
- 20. 1.2007 17:02:22
-
Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014)
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- Date
- 18. 3.2014 19:13:22
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Chen, C.-M.: Classification of scientific networks using aggregated journal-journal citation relations in the Journal Citation Reports (2008)
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- Abstract
- I propose an approach to classifying scientific networks in terms of aggregated journal-journal citation relations of the ISI Journal Citation Reports using the affinity propagation method. This algorithm is applied to obtain the classification of SCI and SSCI journals by minimizing intracategory journal-journal (J-J) distances in the database, where distance between journals is calculated from the similarity of their annual citation patterns with a cutoff parameter, t, to restrain the maximal J-J distance. As demonstrated in the classification of SCI journals, classification of scientific networks with different resolution is possible by choosing proper values of t. Twenty journal categories in SCI are found to be stable despite a difference of an order of magnitude in t. In our classifications, the level of specificity of a category can be found by looking at its value of RJ (the average distance of members of a category to its representative journal), and relatedness of category members is implied by the value of DJ-J (the average DJ-J distance within a category). Our results are consistent with the ISI classification scheme, and the level of relatedness for most categories in our classification is higher than their counterpart in the ISI classification scheme.
-
Rao, I.K.: ¬The distribution of scientific productivity and social change (1978)
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- Abstract
- Results in the literature concerning the probability that an author publishes r articles in time t are reexamined, and it is found that a negative binomial distribution bits scientific productivity data (by the chi-squared goodness-of-fit-test) better than many other distribution such as geometric, logarithmic, zeta, cumulative advantage, etc. It is shown analytically that the nagative binomial distribution describes a pattern of scientific productivity under the 'success-breeds-success' condition in a wide variety of social circumstances
-
Luukkonen, T.: Why has Latour's theory of citation been ignored by the bibliometric community? : Discussion od sociological interpretations of citation analysis (1997)
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-
Burrell, Q.L.: Will this paper ever be cited? (2002)
0.02
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- Abstract
- A recently proposed stochastic model to describe the citation process in the presence of obsolescence is used to answer the question: If a paper has not been cited by time t after its publication, what is the probability that it will ever be cited?
-
Marchant, T.: Score-based bibliometric rankings of authors (2009)
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-
Tscherteu, G.; Langreiter, C.: Explorative Netzwerkanalyse im Living Web (2009)
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- Source
- Social Semantic Web: Web 2.0, was nun? Hrsg.: A. Blumauer u. T. Pellegrini
-
Renn, O.; Schnabl, J.: Forschungsmetriken: Ignorieren, boykottieren oder nutzen? : Forschungsmetriken in die Praxis gebracht (2017)
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- Content
- Vgl.: https://www.b-i-t-online.de/heft/2017-03-index.php.
-
Khan, G.F.; Park, H.W.: Measuring the triple helix on the web : longitudinal trends in the university-industry-government relationship in Korea (2011)
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- Abstract
- This study examines longitudinal trends in the university-industry-government (UIG) relationship on the web in the Korean context by using triple helix (TH) indicators. The study considers various Internet resources, including websites/documents, blogs, online cafes, Knowledge-In (comparable to Yahoo! Answers), and online news sites, by employing webometric and co-word analysis techniques to ascertain longitudinal trends in the UIG relationship, which have received considerable attention in the last decade. The results indicate that the UIG relationship varied according to the government's policies and that there was some tension in the longitudinal UIG relationship. Further, websites/documents and blogs were the most reliable sources for examining the strength of and variations in the bilateral and trilateral UIG relationships on the web. In addition, web-based T(uig) values showed a stronger trilateral relationship and larger variations in the UIG relationship than Science Citation Index-based T(uig) values. The results suggest that various Internet resources (e.g., advanced search engines, websites/documents, blogs, and online cafes), together with TH indicators, can be used to explore the UIG relationship on the web.
-
Braun, T.; Glanzel, W.; Grupp, H.: ¬The scientometric weight of 50 nations in 27 scientific areas, 1989-1993 : Pt.1: All fields combined, mathematics, engineering, chemistry and physics (1995)
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-
Bookstein, A.; Raita, T.: Discovering term occurence structure in text (2001)
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-
Liang, L.: R-Sequences : relative indicators for the rhythm of science (2005)
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- Abstract
- Like most activities in the world, scientific evolution has its own rhythm. How can this evolutionary rhythm be described and made visible? Do different fields have different rhythms, and how can they be measured? In order to answer these questions a relative indicator, called R-sequence, was designed. This indicator is time dependent, derived from publication and citation data, but independent of the absolute number of publications, as weIl as the absolute number of citations, and can therefore be used in a comparison of different scientific fields, nations, Institutes, or journals. Two caiculation methods of the R-sequence-the triangle method and the parallelogram method-are introduced. As a case study JASIS(T)'s R-sequence has been obtained.
-
Brody, T.; Harnad, S.; Carr, L.: Earlier Web usage statistics as predictors of later citation impact (2006)
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Lafouge, T.; Prime-Claverie, C.: Production and use of information : Characterization of informetric distributions using effort function and density function. Exponential informetric process (2005)
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