Search (250 results, page 1 of 13)

  • × theme_ss:"Informetrie"
  1. Koehler, W.: Web page change and persistence : a four-year longitudinal study (2002) 0.13 
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    Abstract
    Changes in the topography of the Web can be expressed in at least four ways: (1) more sites on more servers in more places, (2) more pages and objects added to existing sites and pages, (3) changes in traffic, and (4) modifications to existing text, graphic, and other Web objects. This article does not address the first three factors (more sites, more pages, more traffic) in the growth of the Web. It focuses instead on changes to an existing set of Web documents. The article documents changes to an aging set of Web pages, first identified and "collected" in December 1996 and followed weekly thereafter. Results are reported through February 2001. The article addresses two related phenomena: (1) the life cycle of Web objects, and (2) changes to Web objects. These data reaffirm that the half-life of a Web page is approximately 2 years. There is variation among Web pages by top-level domain and by page type (navigation, content). Web page content appears to stabilize over time; aging pages change less often than once they did
    Date
    7. 2.2002 20:13:03
  2. Ridenour, L.: Boundary objects : measuring gaps and overlap between research areas (2016) 0.10 
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    Abstract
    The aim of this paper is to develop methodology to determine conceptual overlap between research areas. It investigates patterns of terminology usage in scientific abstracts as boundary objects between research specialties. Research specialties were determined by high-level classifications assigned by Thomson Reuters in their Essential Science Indicators file, which provided a strictly hierarchical classification of journals into 22 categories. Results from the query "network theory" were downloaded from the Web of Science. From this file, two top-level groups, economics and social sciences, were selected and topically analyzed to provide a baseline of similarity on which to run an informetric analysis. The Places & Spaces Map of Science (Klavans and Boyack 2007) was used to determine the proximity of disciplines to one another in order to select the two disciplines use in the analysis. Groups analyzed share common theories and goals; however, groups used different language to describe their research. It was found that 61% of term words were shared between the two groups.
  3. Scholarly metrics under the microscope : from citation analysis to academic auditing (2015) 0.07 
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    Classification
    010.72/7 / dc23
    Date
    22. 1.2017 17:12:50
    DDC
    010.72/7 / dc23
  4. Egghe, L.: Type/Token-Taken informetrics (2003) 0.06 
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    Abstract
    Type/Token-Taken informetrics is a new part of informetrics that studies the use of items rather than the items itself. Here, items are the objects that are produced by the sources (e.g., journals producing articles, authors producing papers, etc.). In linguistics a source is also called a type (e.g., a word), and an item a token (e.g., the use of words in texts). In informetrics, types that occur often, for example, in a database will also be requested often, for example, in information retrieval. The relative use of these occurrences will be higher than their relative occurrences itself; hence, the name Type/ Token-Taken informetrics. This article studies the frequency distribution of Type/Token-Taken informetrics, starting from the one of Type/Token informetrics (i.e., source-item relationships). We are also studying the average number my* of item uses in Type/Token-Taken informetrics and compare this with the classical average number my in Type/Token informetrics. We show that my* >= my always, and that my* is an increasing function of my. A method is presented to actually calculate my* from my, and a given a, which is the exponent in Lotka's frequency distribution of Type/Token informetrics. We leave open the problem of developing non-Lotkaian Type/TokenTaken informetrics.
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.7, S.603-610
  5. Järvelin, K.; Vakkari, P.: LIS research across 50 years: content analysis of journal articles : offering an information-centric conception of memes (2022) 0.06 
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    Abstract
    Purpose This paper analyses the research in Library and Information Science (LIS) and reports on (1) the status of LIS research in 2015 and (2) on the evolution of LIS research longitudinally from 1965 to 2015. Design/methodology/approach The study employs a quantitative intellectual content analysis of articles published in 30+ scholarly LIS journals, following the design by Tuomaala et al. (2014). In the content analysis, we classify articles along eight dimensions covering topical content and methodology. Findings The topical findings indicate that the earlier strong LIS emphasis on L&I services has declined notably, while scientific and professional communication has become the most popular topic. Information storage and retrieval has given up its earlier strong position towards the end of the years analyzed. Individuals are increasingly the units of observation. End-user's and developer's viewpoints have strengthened at the cost of intermediaries' viewpoint. LIS research is methodologically increasingly scattered since survey, scientometric methods, experiment, case studies and qualitative studies have all gained in popularity. Consequently, LIS may have become more versatile in the analysis of its research objects during the years analyzed. Originality/value Among quantitative intellectual content analyses of LIS research, the study is unique in its scope: length of analysis period (50 years), width (8 dimensions covering topical content and methodology) and depth (the annual batch of 30+ scholarly journals).
    Source
    Journal of documentation. 78(2022) no.7, S.65-88
  6. Haustein, S.; Sugimoto, C.; Larivière, V.: Social media in scholarly communication : Guest editorial (2015) 0.04 
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    Abstract
    There will soon be a critical mass of web-based digital objects and usage statistics on which to model scholars' communication behaviors - publishing, posting, blogging, scanning, reading, downloading, glossing, linking, citing, recommending, acknowledging - and with which to track their scholarly influence and impact, broadly conceived and broadly felt (Cronin, 2005, p. 196). A decade after Cronin's prediction and five years after the coining of altmetrics, the time seems ripe to reflect upon the role of social media in scholarly communication. This Special Issue does so by providing an overview of current research on the indicators and metrics grouped under the umbrella term of altmetrics, on their relationships with traditional indicators of scientific activity, and on the uses that are made of the various social media platforms - on which these indicators are based - by scientists of various disciplines.
    Date
    20. 1.2015 18:30:22
  7. Mukherjee, B.: Do open-access journals in library and information science have any scholarly impact? : a bibliometric study of selected open-access journals using Google Scholar (2009) 0.04 
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    Abstract
    Using 17 fully open-access journals published uninterruptedly during 2000 to 2004 in the field of library and information science, the present study investigates the impact of these open-access journals in terms of quantity of articles published, subject distribution of the articles, synchronous and diachronous impact factor, immediacy index, and journals' and authors' self-citation. The results indicate that during this 5-year publication period, there are as many as 1,636 articles published by these journals. At the same time, the articles have received a total of 8,591 Web citations during a 7-year citation period. Eight of 17 journals have received more than 100 citations. First Monday received the highest number of citations; however, the average number of citations per article was the highest in D-Lib Magazine. The value of the synchronous impact factor varies from 0.6989 to 1.0014 during 2002 to 2005, and the diachronous impact factor varies from 1.472 to 2.487 during 2000 to 2004. The range of the immediacy index varies between 0.0714 and 1.395. D-Lib Magazine has an immediacy index value above 0.5 in all the years whereas the immediacy index value varies from year to year for the other journals. When the citations of sample articles were analyzed according to source, it was found that 40.32% of the citations came from full-text articles, followed by 33.35% from journal articles. The percentage of journals' self-citation was only 6.04%.
    Date
    22. 3.2009 17:54:59
  8. Asubiaro, T.V.; Onaolapo, S.: ¬A comparative study of the coverage of African journals in Web of Science, Scopus, and CrossRef (2023) 0.04 
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    Date
    22. 6.2023 14:09:06
    Source
    Journal of the Association for Information Science and Technology. 74(2023) no.7, S.745-758
  9. Zhang, Y.; Wu, M.; Zhang, G.; Lu, J.: Stepping beyond your comfort zone : diffusion-based network analytics for knowledge trajectory recommendation (2023) 0.04 
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    Date
    22. 6.2023 18:07:12
    Source
    Journal of the Association for Information Science and Technology. 74(2023) no.7, S.775-790
  10. Thelwall, M.; Kousha, K.; Abdoli, M.; Stuart, E.; Makita, M.; Wilson, P.; Levitt, J.: Why are coauthored academic articles more cited : higher quality or larger audience? (2023) 0.04 
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    Date
    22. 6.2023 18:11:50
    Source
    Journal of the Association for Information Science and Technology. 74(2023) no.7, S.791-810
  11. Vakkari, P.; Järvelin, K.; Chang, Y.-W.: ¬The association of disciplinary background with the evolution of topics and methods in Library and Information Science research 1995-2015 (2023) 0.04 
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    Date
    22. 6.2023 18:15:06
    Source
    Journal of the Association for Information Science and Technology. 74(2023) no.7, S.811-827
  12. Xu, C.; Ma, B.; Chen, X.; Ma, F.: Social tagging in the scholarly world (2013) 0.03 
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    Abstract
    The number of research studies on social tagging has increased rapidly in the past years, but few of them highlight the characteristics and research trends in social tagging. A set of 862 academic documents relating to social tagging and published from 2005 to 2011 was thus examined using bibliometric analysis as well as the social network analysis technique. The results show that social tagging, as a research area, develops rapidly and attracts an increasing number of new entrants. There are no key authors, publication sources, or research groups that dominate the research domain of social tagging. Research on social tagging appears to focus mainly on the following three aspects: (a) components and functions of social tagging (e.g., tags, tagging objects, and tagging network), (b) taggers' behaviors and interface design, and (c) tags' organization and usage in social tagging. The trend suggest that more researchers turn to the latter two integrated with human computer interface and information retrieval, although the first aspect is the fundamental one in social tagging. Also, more studies relating to social tagging pay attention to multimedia tagging objects and not only text tagging. Previous research on social tagging was limited to a few subject domains such as information science and computer science. As an interdisciplinary research area, social tagging is anticipated to attract more researchers from different disciplines. More practical applications, especially in high-tech companies, is an encouraging research trend in social tagging.
  13. Nicholls, P.T.: Empirical validation of Lotka's law (1986) 0.03 
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    Source
    Information processing and management. 22(1986), S.417-419
  14. Nicolaisen, J.: Citation analysis (2007) 0.03 
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    Date
    13. 7.2008 19:53:22
  15. Fiala, J.: Information flood : fiction and reality (1987) 0.03 
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    Source
    Thermochimica acta. 110(1987), S.11-22
  16. Schneider, J.W.; Borlund, P.: Matrix comparison, part 1 : motivation and important issues for measuring the resemblance between proximity measures or ordination results (2007) 0.03 
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    Abstract
    The present two-part article introduces matrix comparison as a formal means of evaluation in informetric studies such as cocitation analysis. In this first part, the motivation behind introducing matrix comparison to informetric studies, as well as two important issues influencing such comparisons, are introduced and discussed. The motivation is spurred by the recent debate on choice of proximity measures and their potential influence upon clustering and ordination results. The two important issues discussed here are matrix generation and the composition of proximity measures. The approach to matrix generation is demonstrated for the same data set, i.e., how data is represented and transformed in a matrix, evidently determines the behavior of proximity measures. Two different matrix generation approaches, in all probability, will lead to different proximity rankings of objects, which further lead to different ordination and clustering results for the same set of objects. Further, a resemblance in the composition of formulas indicates whether two proximity measures may produce similar ordination and clustering results. However, as shown in the case of the angular correlation and cosine measures, a small deviation in otherwise similar formulas can lead to different rankings depending on the contour of the data matrix transformed. Eventually, the behavior of proximity measures, that is whether they produce similar rankings of objects, is more or less data-specific. Consequently, the authors recommend the use of empirical matrix comparison techniques for individual studies to investigate the degree of resemblance between proximity measures or their ordination results. In part two of the article, the authors introduce and demonstrate two related statistical matrix comparison techniques the Mantel test and Procrustes analysis, respectively. These techniques can compare and evaluate the degree of monotonicity between different proximity measures or their ordination results. As such, the Mantel test and Procrustes analysis can be used as statistical validation tools in informetric studies and thus help choosing suitable proximity measures.
  17. Small, H.; Sweeney, E.: Clustering the Science Citation Index using co-citations (1985) 0.03 
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    Source
    Scientometrics. 7(1985), S.391-409
  18. Su, Y.; Han, L.-F.: ¬A new literature growth model : variable exponential growth law of literature (1998) 0.03 
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    Date
    22. 5.1999 19:22:35
  19. Van der Veer Martens, B.: Do citation systems represent theories of truth? (2001) 0.03 
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    Date
    22. 7.2006 15:22:28
  20. Diodato, V.: Dictionary of bibliometrics (1994) 0.03 
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    Footnote
    Rez. in: Journal of library and information science 22(1996) no.2, S.116-117 (L.C. Smith)

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