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  • × theme_ss:"Informetrie"
  • × year_i:[2000 TO 2010}
  1. Chen, C.: CiteSpace II : detecting and visualizing emerging trends and transient patterns in scientific literature (2006) 0.02 
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    Abstract
    This article describes the latest development of a generic approach to detecting and visualizing emerging trends and transient patterns in scientific literature. The work makes substantial theoretical and methodological contributions to progressive knowledge domain visualization. A specialty is conceptualized and visualized as a time-variant duality between two fundamental concepts in information science: research fronts and intellectual bases. A research front is defined as an emergent and transient grouping of concepts and underlying research issues. The intellectual base of a research front is its citation and co-citation footprint in scientific literature - an evolving network of scientific publications cited by research-front concepts. Kleinberg's (2002) burst-detection algorithm is adapted to identify emergent research-front concepts. Freeman's (1979) betweenness centrality metric is used to highlight potential pivotal points of paradigm shift over time. Two complementary visualization views are designed and implemented: cluster views and time-zone views. The contributions of the approach are that (a) the nature of an intellectual base is algorithmically and temporally identified by emergent research-front terms, (b) the value of a co-citation cluster is explicitly interpreted in terms of research-front concepts, and (c) visually prominent and algorithmically detected pivotal points substantially reduce the complexity of a visualized network. The modeling and visualization process is implemented in CiteSpace II, a Java application, and applied to the analysis of two research fields: mass extinction (1981-2004) and terrorism (1990-2003). Prominent trends and pivotal points in visualized networks were verified in collaboration with domain experts, who are the authors of pivotal-point articles. Practical implications of the work are discussed. A number of challenges and opportunities for future studies are identified.
    Date
    22. 7.2006 16:11:05
    Type
    a
  2. H-Index auch im Web of Science (2008) 0.02 
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    Date
    6. 4.2008 19:04:22
    Type
    a
  3. Meho, L.I.; Rogers, Y.: Citation counting, citation ranking, and h-index of human-computer interaction researchers : a comparison of Scopus and Web of Science (2008) 0.02 
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    Abstract
    This study examines the differences between Scopus and Web of Science in the citation counting, citation ranking, and h-index of 22 top human-computer interaction (HCI) researchers from EQUATOR - a large British Interdisciplinary Research Collaboration project. Results indicate that Scopus provides significantly more coverage of HCI literature than Web of Science, primarily due to coverage of relevant ACM and IEEE peer-reviewed conference proceedings. No significant differences exist between the two databases if citations in journals only are compared. Although broader coverage of the literature does not significantly alter the relative citation ranking of individual researchers, Scopus helps distinguish between the researchers in a more nuanced fashion than Web of Science in both citation counting and h-index. Scopus also generates significantly different maps of citation networks of individual scholars than those generated by Web of Science. The study also presents a comparison of h-index scores based on Google Scholar with those based on the union of Scopus and Web of Science. The study concludes that Scopus can be used as a sole data source for citation-based research and evaluation in HCI, especially when citations in conference proceedings are sought, and that researchers should manually calculate h scores instead of relying on system calculations.
    Type
    a
  4. Costas, R.; Bordons, M.; Leeuwen, T.N. van; Raan, A.F.J. van: Scaling rules in the science system : Influence of field-specific citation characteristics on the impact of individual researchers (2009) 0.02 
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    Abstract
    The representation of science as a citation density landscape and the study of scaling rules with the field-specific citation density as a main topological property was previously analyzed at the level of research groups. Here, the focus is on the individual researcher. In this new analysis, the size dependence of several main bibliometric indicators for a large set of individual researchers is explored. Similar results as those previously observed for research groups are described for individual researchers. The total number of citations received by scientists increases in a cumulatively advantageous way as a function of size (in terms of number of publications) for researchers in three areas: Natural Resources, Biology & Biomedicine, and Materials Science. This effect is stronger for researchers in low citation density fields. Differences found among thematic areas with different citation densities are discussed.
    Date
    22. 3.2009 19:02:48
    Type
    a
  5. Kousha, K.; Thelwall, M.: How is science cited on the Web? : a classification of google unique Web citations (2007) 0.02 
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    Abstract
    Although the analysis of citations in the scholarly literature is now an established and relatively well understood part of information science, not enough is known about citations that can be found on the Web. In particular, are there new Web types, and if so, are these trivial or potentially useful for studying or evaluating research communication? We sought evidence based upon a sample of 1,577 Web citations of the URLs or titles of research articles in 64 open-access journals from biology, physics, chemistry, and computing. Only 25% represented intellectual impact, from references of Web documents (23%) and other informal scholarly sources (2%). Many of the Web/URL citations were created for general or subject-specific navigation (45%) or for self-publicity (22%). Additional analyses revealed significant disciplinary differences in the types of Google unique Web/URL citations as well as some characteristics of scientific open-access publishing on the Web. We conclude that the Web provides access to a new and different type of citation information, one that may therefore enable us to measure different aspects of research, and the research process in particular; but to obtain good information, the different types should be separated.
    Type
    a
  6. Shibata, N.; Kajikawa, Y.; Takeda, Y.; Matsushima, K.: Comparative study on methods of detecting research fronts using different types of citation (2009) 0.02 
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    Abstract
    In this article, we performed a comparative study to investigate the performance of methods for detecting emerging research fronts. Three types of citation network, co-citation, bibliographic coupling, and direct citation, were tested in three research domains, gallium nitride (GaN), complex network (CNW), and carbon nanotube (CNT). Three types of citation network were constructed for each research domain, and the papers in those domains were divided into clusters to detect the research front. We evaluated the performance of each type of citation network in detecting a research front by using the following measures of papers in the cluster: visibility, measured by normalized cluster size, speed, measured by average publication year, and topological relevance, measured by density. Direct citation, which could detect large and young emerging clusters earlier, shows the best performance in detecting a research front, and co-citation shows the worst. Additionally, in direct citation networks, the clustering coefficient was the largest, which suggests that the content similarity of papers connected by direct citations is the greatest and that direct citation networks have the least risk of missing emerging research domains because core papers are included in the largest component.
    Date
    22. 3.2009 17:52:50
    Type
    a
  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) 0.02 
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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
    Type
    a
  8. Hayer, L.: Lazarsfeld zitiert : eine bibliometrische Analyse (2008) 0.02 
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    Abstract
    Um sich einer Antwort auf die Frage anzunähern, welche Bedeutung der Nachlass eines Wissenschaftlers wie jener Paul F. Lazarsfelds (mit zahlreichen noch unveröffentlichten Schriften) für die aktuelle Forschung haben könne, kann untersucht werden, wie häufig dieser Wissenschaftler zitiert wird. Wenn ein Autor zitiert wird, wird er auch genutzt. Wird er über einen langen Zeitraum oft genutzt, ist vermutlich auch die Auseinandersetzung mit seinem Nachlass von Nutzen. Außerdem kann aufgrund der Zitierungen festgestellt werden, was aus dem Lebenswerk eines Wissenschaftlers für die aktuelle Forschung relevant erscheint. Daraus können die vordringlichen Fragestellungen in der Bearbeitung des Nachlasses abgeleitet werden. Die Aufgabe für die folgende Untersuchung lautete daher: Wie oft wird Paul F. Lazarsfeld zitiert? Dabei interessierte auch: Wer zitiert wo? Die Untersuchung wurde mit Hilfe der Meta-Datenbank "ISI Web of Knowledge" durchgeführt. In dieser wurde im "Web of Science" mit dem Werkzeug "Cited Reference Search" nach dem zitierten Autor (Cited Author) "Lazarsfeld P*" gesucht. Diese Suche ergab 1535 Referenzen (References). Werden alle Referenzen gewählt, führt dies zu 4839 Ergebnissen (Results). Dabei wurden die Datenbanken SCI-Expanded, SSCI und A&HCI verwendet. Bei dieser Suche wurden die Publikationsjahre 1941-2008 analysiert. Vor 1956 wurden allerdings nur sehr wenige Zitate gefunden: 1946 fünf, ansonsten maximal drei, 1942-1944 und 1949 überhaupt keines. Zudem ist das Jahr 2008 noch lange nicht zu Ende. (Es gab jedoch schon vor Ende März 24 Zitate!)
    Date
    22. 6.2008 12:54:12
    Type
    a
  9. Ball, R.: Wissenschaftsindikatoren im Zeitalter digitaler Wissenschaft (2007) 0.02 
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    Date
    23.12.2007 19:22:21
    Type
    a
  10. Tonta, Y.; Ünal, Y.: Scatter of journals and literature obsolescence reflected in document delivery requests (2005) 0.02 
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    Abstract
    In this paper we investigate the scattering of journals and literature obsolescence reflected in more than 137,000 document delivery requests submitted to a national document delivery service. We first summarize the major findings of the study with regards to the performance of the service. We then identify the "core" journals from which article requests were satisfied and address the following research questions: (a) Does the distribution of (core) journals conform to the Bradford's Law of Scattering? (b) Is there a relationship between usage of journals and impact factors, journals with high impact factors being used more often than the rest? (c) Is there a relationship between usage of journals and total citation counts, journals with high total citation counts being used more often than the rest? (d) What is the median age of use (half-life) of requested articles in general? (e) Do requested articles that appear in core journals get obsolete more slowly? (f) Is there a relationship between obsolescence and journal impact factors, journals with high impact factors being obsolete more slowly? (g) Is there a relationship between obsolescence and total citation counts, journals with high total citation counts being obsolete more slowly? Based an the analysis of findings, we found that the distribution of highly and moderately used journal titles conform to Bradford's Law. The median age of use was 8 years for all requested articles. Ninety percent of the articles requested were 21 years of age or younger. Articles that appeared in 168 core journal titles seem to get obsolete slightly more slowly than those of all titles. We observed no statistically significant correlations between the frequency of journal use and ISI journal impact factors, and between the frequency of journal use and ISI- (Institute for Scientific Information, Philadelphia, PA) cited half-lives for the most heavily used 168 core journal titles. There was a weak correlation between usage of journals and ISI-reported total citation counts. No statistically significant relationship was found between median age of use and journal impact factors and between median age of use and total citation counts. There was a weak negative correlation between ISI journal impact factors and cited half-lives of 168 core journals, and a weak correlation between ISI citation halflives and use half-lives of core journals. No correlation was found between cited half-lives of 168 core journals and their corresponding total citation counts as reported by ISI. Findings of the current study are discussed along with those of other studies.
    Date
    20. 3.2005 10:54:22
    Type
    a
  11. Ahlgren, P.; Jarneving, B.; Rousseau, R.: Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient (2003) 0.01 
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    Abstract
    Ahlgren, Jarneving, and. Rousseau review accepted procedures for author co-citation analysis first pointing out that since in the raw data matrix the row and column values are identical i,e, the co-citation count of two authors, there is no clear choice for diagonal values. They suggest the number of times an author has been co-cited with himself excluding self citation rather than the common treatment as zeros or as missing values. When the matrix is converted to a similarity matrix the normal procedure is to create a matrix of Pearson's r coefficients between data vectors. Ranking by r and by co-citation frequency and by intuition can easily yield three different orders. It would seem necessary that the adding of zeros to the matrix will not affect the value or the relative order of similarity measures but it is shown that this is not the case with Pearson's r. Using 913 bibliographic descriptions form the Web of Science of articles form JASIS and Scientometrics, authors names were extracted, edited and 12 information retrieval authors and 12 bibliometric authors each from the top 100 most cited were selected. Co-citation and r value (diagonal elements treated as missing) matrices were constructed, and then reconstructed in expanded form. Adding zeros can both change the r value and the ordering of the authors based upon that value. A chi-squared distance measure would not violate these requirements, nor would the cosine coefficient. It is also argued that co-citation data is ordinal data since there is no assurance of an absolute zero number of co-citations, and thus Pearson is not appropriate. The number of ties in co-citation data make the use of the Spearman rank order coefficient problematic.
    Date
    9. 7.2006 10:22:35
    Type
    a
  12. Wettlauf der Wissenschaft (2004) 0.01 
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    Source
    Online Mitteilungen. 2004, Nr.79, S.22-23 [=Mitteilungen VÖB 57(2004) H.2]
    Type
    a
  13. Egghe, L.: Untangling Herdan's law and Heaps' law : mathematical and informetric arguments (2007) 0.00 
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    Abstract
    Herdan's law in linguistics and Heaps' law in information retrieval are different formulations of the same phenomenon. Stated briefly and in linguistic terms they state that vocabularies' sizes are concave increasing power laws of texts' sizes. This study investigates these laws from a purely mathematical and informetric point of view. A general informetric argument shows that the problem of proving these laws is, in fact, ill-posed. Using the more general terminology of sources and items, the author shows by presenting exact formulas from Lotkaian informetrics that the total number T of sources is not only a function of the total number A of items, but is also a function of several parameters (e.g., the parameters occurring in Lotka's law). Consequently, it is shown that a fixed T(or A) value can lead to different possible A (respectively, T) values. Limiting the T(A)-variability to increasing samples (e.g., in a text as done in linguistics) the author then shows, in a purely mathematical way, that for large sample sizes T~ A**phi, where phi is a constant, phi < 1 but close to 1, hence roughly, Heaps' or Herdan's law can be proved without using any linguistic or informetric argument. The author also shows that for smaller samples, a is not a constant but essentially decreases as confirmed by practical examples. Finally, an exact informetric argument on random sampling in the items shows that, in most cases, T= T(A) is a concavely increasing function, in accordance with practical examples.
    Type
    a
  14. Harzing, A.-W.; Wal, R. van der: ¬A Google Scholar h-index for journals : an alternative metric to measure journal impact in economics and business (2009) 0.00 
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    Abstract
    We propose a new data source (Google Scholar) and metric (Hirsch's h-index) to assess journal impact in the field of economics and business. A systematic comparison between the Google Scholar h-index and the ISI Journal Impact Factor for a sample of 838 journals in economics and business shows that the former provides a more accurate and comprehensive measure of journal impact.
    Type
    a
  15. Egghe, L.: ¬A rationale for the Hirsch-index rank-order distribution and a comparison with the impact factor rank-order distribution (2009) 0.00 
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    Abstract
    We present a rationale for the Hirsch-index rank-order distribution and prove that it is a power law (hence a straight line in the log-log scale). This is confirmed by experimental data of Pyykkö and by data produced in this article on 206 mathematics journals. This distribution is of a completely different nature than the impact factor (IF) rank-order distribution which (as proved in a previous article) is S-shaped. This is also confirmed by our example. Only in the log-log scale of the h-index distribution do we notice a concave deviation of the straight line for higher ranks. This phenomenon is discussed.
    Type
    a
  16. Sotudeh, H.; Horri, A.: ¬The citation performance of open access journals : a disciplinary investigation of citation distribution models (2007) 0.00 
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  17. Torvik, V.I.; Weeber, M.; Swanson, D.R.; Smalheiser, N.R.: ¬A probabilistic similarity metric for medline mecords : a model for author name disambiguation (2005) 0.00 
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    Abstract
    We present a model for estimating the probability that a pair of author names (sharing last name and first initial), appearing an two different Medline articles, refer to the same individual. The model uses a simple yet powerful similarity profile between a pair of articles, based an title, journal name, coauthor names, medical subject headings (MeSH), language, affiliation, and name attributes (prevalence in the literature, middle initial, and suffix). The similarity profile distribution is computed from reference sets consisting of pairs of articles containing almost exclusively author matches versus nonmatches, generated in an unbiased manner. Although the match set is generated automatically and might contain a small proportion of nonmatches, the model is quite robust against contamination with nonmatches. We have created a free, public service ("Author-ity": http://arrowsmith.psych.uic.edu) that takes as input an author's name given an a specific article, and gives as output a list of all articles with that (last name, first initial) ranked by decreasing similarity, with match probability indicated.
    Type
    a
  18. Christoffersen, M.: Identifying core documents with a multiple evidence relevance filter (2004) 0.00 
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  19. He, Y.; Hui, S.C.: Mining a web database for author cocitation analysis (2002) 0.00 
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  20. Liu, Z.; Wang, C.: Mapping interdisciplinarity in demography : a journal network analysis (2005) 0.00 
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Authors

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  • m 2
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