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Abstract

A scientometric model (ISI-S model) is introduced for describing the institutionalization process of scientific information. The central concept of ISI-S is that the scientific information published may develop with time through permanent evaluation and modification processes toward a cognitive consensus of distinguished authors of the respective scientific field or discipline. ISI-S describes the information and knowledge systems of science as a global network of interdependent information and knowledge clusters that are dynamically changing by their content and size. ISI-S assumes sets of information with short- or long-term impact and information integrated into the basic scientific knowledge or common knowledge. The type of the information sources (e.g., lecture, journal paper, review, monograph, book, textbook, lexicon) and the length of the impact are related to the grade of institutionalization. References are considered as proofs of manifested impact. The relative and absolute development of scientific knowledge seems to be slower than the increase of the number of publications.

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Abstract

The Garfield (Impact) Factor (GF) is one of the most frequently used scientometric indicators. In the present article it is shown that the main factors determining the value of the mean GF representing a set of journals are the number of articles published recently (articles referencing) related to those published in a previous time period (articles to be referenced) and the mean number of references in journal papers referring to the time period selected. It has been proved further that GF corresponds to the mean chance for citedness of journal papers. A new indicator, Specific Impact Contribution (SIC), is introduced, which characterizes the contribution of a subset of articles or a journal to the total impact of the respective articles or journals. The SIC Index relates the share of a journal in citations divided by that in publications within a set of papers or journals appropriately selected. It is shown, however, that the normalized GFs of journals and the normalized SIC indicators are identical measures within any set of journals selected. It may be stated therefore that Garfield Factors of journals (calculated correctly) are appropriate scientometric measures for characterizing the relative international eminence of journals within a set of journals appropriately selected. It is demonstrated further that SIC indicators (and so GF indexes) correspond to the (number of citations per paper) indicators generally used, within the same set of papers.

Source

Journal of the American Society for Information Science and technology. 55(2004) no.5, S.431-435

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Abstract

The ?-indicator (or ?v-indicator) of a set of journal papers is equal to a hundredth of the total number of citations obtained by the elite set of publications. The number of publications in the elite set P(?) is calculated as the square root of total papers. For greater sets the following equation is used: P(?v) = (10 log P) - 10, where P is the total number of publications. For sets comprising a single or several extreme frequently cited paper, the ?-index may be distorted. Therefore, a new indicator based on the distribution of citations is suggested. Accordingly, the publications are classified into citation categories, of which lower limits are given as 0, and (2n + 1), whereas the upper limits as 2n (n = 0, 2, 3, etc.). The citations distribution score (CDS) index is defined as the sum of weighted numbers of publications in the individual categories. The CDS-index increases logarithmically with the increasing number of citations. The citation distribution rate indicator is introduced by relating the actual CDS-index to the possible maximum. Several size-dependent and size-independent indicators were calculated. It has been concluded that relevant, already accepted scientometric indicators may validate novel indices through resulting in similar conclusions ("converging validation of indicators").

Source

Journal of the American Society for Information Science and Technology. 62(2011) no.10, S.1963-1978

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Abstract

In the present stage of scientometrics, indicators published are mostly incomparable, which fact impedes the development of the field and makes the users of scientometric results mistrustful. Consequently, standardization of data, methods, indicators and their presentation is urgently needed. For instance, the time periods applied should be standardized across fields and subfields in calculating citation and publication indicators

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Abstract

The publication performance of 30 scientometricians is studied. The individuals are classified into 3 cohorts according to their manifested professional recognition, as Price medalists (Pm), members of the editorial board of Scientometrics and the Journal of Informetrics (Rw), and session chairs (Sc) at an International Society of Scientometrics and Informetrics (ISSI) conference. Several core impact indicators are calculated: h, g, p, citation distribution score (CDS), percentage rank position (PRP), and weight of influence of papers (WIP10). The indices significantly correlate with each other. The mean value of the indices of the cohorts decreases parallel with the decrease in professional recognition: Pm?>?Rw?>?Sc. The 30 scientometricians studied were clustered according to the core impact indices. The members in the clusters so obtained overlap only partly with the members in the cohorts made by professional recognition. The Total Overlap is calculated by dividing the sum of the diagonal elements in the cohorts-clusters matrix with the total number of elements, times 100. The highest overlap (76.6%) was obtained with the g-index. Accordingly, the g-index seems to have the greatest discriminative power in the system studied. The cohorts-clusters method may be used for validating scientometric indicators.

Source

Journal of the Association for Information Science and Technology. 68(2017) no.1, S.234-242

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Abstract

Chances for information to be cited (CC) depend on disciplines and topics because of different publication and referencing practices. However, the developmental rate of knowledge strongly influences CC as well. By a simple model concludes that CC are the greater the faster the publication rate

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Source

Journal of the American Society for Information Science and Technology. 64(2013) no.5, S.1084-1085