Search (24 results, page 1 of 2)

  • × author_ss:"Thelwall, M."
  • × theme_ss:"Informetrie"
  • × year_i:[2000 TO 2010}
  1. Levitt, J.M.; Thelwall, M.: Citation levels and collaboration within library and information science (2009) 0.03 
    0.026092373 = product of:
  0.08871406 = sum of:
    0.013703404 = product of:
      0.027406808 = sum of:
        0.027406808 = weight(_text_:bibliothekswesen in 2734) [ClassicSimilarity], result of:
          0.027406808 = score(doc=2734,freq=2.0), product of:
            0.11129492 = queryWeight, product of:
              4.457672 = idf(docFreq=1392, maxDocs=44218)
              0.024967048 = queryNorm
            0.24625391 = fieldWeight in 2734, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.457672 = idf(docFreq=1392, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2734)
      0.5 = coord(1/2)
    0.027988197 = weight(_text_:informationswissenschaft in 2734) [ClassicSimilarity], result of:
      0.027988197 = score(doc=2734,freq=2.0), product of:
        0.11246919 = queryWeight, product of:
          4.504705 = idf(docFreq=1328, maxDocs=44218)
          0.024967048 = queryNorm
        0.24885213 = fieldWeight in 2734, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.504705 = idf(docFreq=1328, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2734)
    0.027406808 = weight(_text_:bibliothekswesen in 2734) [ClassicSimilarity], result of:
      0.027406808 = score(doc=2734,freq=2.0), product of:
        0.11129492 = queryWeight, product of:
          4.457672 = idf(docFreq=1392, maxDocs=44218)
          0.024967048 = queryNorm
        0.24625391 = fieldWeight in 2734, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.457672 = idf(docFreq=1392, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2734)
    0.0076560336 = weight(_text_:in in 2734) [ClassicSimilarity], result of:
      0.0076560336 = score(doc=2734,freq=18.0), product of:
        0.033961542 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.024967048 = queryNorm
        0.22543246 = fieldWeight in 2734, product of:
          4.2426405 = tf(freq=18.0), with freq of:
            18.0 = termFreq=18.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2734)
    0.011959616 = product of:
      0.023919232 = sum of:
        0.023919232 = weight(_text_:22 in 2734) [ClassicSimilarity], result of:
          0.023919232 = score(doc=2734,freq=4.0), product of:
            0.08743035 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.024967048 = queryNorm
            0.27358043 = fieldWeight in 2734, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2734)
      0.5 = coord(1/2)
  0.29411766 = coord(5/17)
    Abstract
    Collaboration is a major research policy objective, but does it deliver higher quality research? This study uses citation analysis to examine the Web of Science (WoS) Information Science & Library Science subject category (IS&LS) to ascertain whether, in general, more highly cited articles are more highly collaborative than other articles. It consists of two investigations. The first investigation is a longitudinal comparison of the degree and proportion of collaboration in five strata of citation; it found that collaboration in the highest four citation strata (all in the most highly cited 22%) increased in unison over time, whereas collaboration in the lowest citation strata (un-cited articles) remained low and stable. Given that over 40% of the articles were un-cited, it seems important to take into account the differences found between un-cited articles and relatively highly cited articles when investigating collaboration in IS&LS. The second investigation compares collaboration for 35 influential information scientists; it found that their more highly cited articles on average were not more highly collaborative than their less highly cited articles. In summary, although collaborative research is conducive to high citation in general, collaboration has apparently not tended to be essential to the success of current and former elite information scientists.
    Date
    22. 3.2009 12:43:51
    Field
    Bibliothekswesen
    Informationswissenschaft
  2. Thelwall, M.; Ruschenburg, T.: Grundlagen und Forschungsfelder der Webometrie (2006) 0.02 
    0.019497072 = product of:
  0.082862556 = sum of:
    0.018776136 = weight(_text_:und in 77) [ClassicSimilarity], result of:
      0.018776136 = score(doc=77,freq=6.0), product of:
        0.055336144 = queryWeight, product of:
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.024967048 = queryNorm
        0.33931053 = fieldWeight in 77, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.0625 = fieldNorm(doc=77)
    0.044781115 = weight(_text_:informationswissenschaft in 77) [ClassicSimilarity], result of:
      0.044781115 = score(doc=77,freq=2.0), product of:
        0.11246919 = queryWeight, product of:
          4.504705 = idf(docFreq=1328, maxDocs=44218)
          0.024967048 = queryNorm
        0.3981634 = fieldWeight in 77, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.504705 = idf(docFreq=1328, maxDocs=44218)
          0.0625 = fieldNorm(doc=77)
    0.0057745427 = weight(_text_:in in 77) [ClassicSimilarity], result of:
      0.0057745427 = score(doc=77,freq=4.0), product of:
        0.033961542 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.024967048 = queryNorm
        0.17003182 = fieldWeight in 77, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0625 = fieldNorm(doc=77)
    0.013530762 = product of:
      0.027061524 = sum of:
        0.027061524 = weight(_text_:22 in 77) [ClassicSimilarity], result of:
          0.027061524 = score(doc=77,freq=2.0), product of:
            0.08743035 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.024967048 = queryNorm
            0.30952093 = fieldWeight in 77, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0625 = fieldNorm(doc=77)
      0.5 = coord(1/2)
  0.23529412 = coord(4/17)
    Abstract
    Die Webometrie ist ein Teilbereich der Informationswissenschaft der zur Zeit auf die Analyse von Linkstrukturen konzentriert ist. Er ist stark von der Zitationsanalyse geprägt, wie der empirische Schwerpunkt auf der Wissenschaftsanalyse zeigt. In diesem Beitrag diskutieren wir die Nutzung linkbasierter Maße in einem breiten informetrischen Kontext und bewerten verschiedene Verfahren, auch im Hinblick auf ihr generelles Potentialfür die Sozialwissenschaften. Dabei wird auch ein allgemeiner Rahmenfür Linkanalysen mit den erforderlichen Arbeitsschritten vorgestellt. Abschließend werden vielversprechende zukünftige Anwendungsfelder der Webometrie benannt, unter besonderer Berücksichtigung der Analyse von Blogs.
    Date
    4.12.2006 12:12:22
    Source
    Information - Wissenschaft und Praxis. 57(2006) H.8, S.401-406
  3. Kousha, K.; Thelwall, M.: How is science cited on the Web? : a classification of google unique Web citations (2007) 0.00 
    0.0016662586 = product of:
  0.014163198 = sum of:
    0.005706471 = weight(_text_:in in 586) [ClassicSimilarity], result of:
      0.005706471 = score(doc=586,freq=10.0), product of:
        0.033961542 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.024967048 = queryNorm
        0.16802745 = fieldWeight in 586, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=586)
    0.008456727 = product of:
      0.016913453 = sum of:
        0.016913453 = weight(_text_:22 in 586) [ClassicSimilarity], result of:
          0.016913453 = score(doc=586,freq=2.0), product of:
            0.08743035 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.024967048 = queryNorm
            0.19345059 = fieldWeight in 586, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=586)
      0.5 = coord(1/2)
  0.11764706 = coord(2/17)
    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.
  4. Levitt, J.M.; Thelwall, M.: Is multidisciplinary research more highly cited? : a macrolevel study (2008) 0.00 
    5.6169135E-4 = product of:
  0.009548753 = sum of:
    0.009548753 = weight(_text_:in in 2375) [ClassicSimilarity], result of:
      0.009548753 = score(doc=2375,freq=28.0), product of:
        0.033961542 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.024967048 = queryNorm
        0.2811637 = fieldWeight in 2375, product of:
          5.2915025 = tf(freq=28.0), with freq of:
            28.0 = termFreq=28.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2375)
  0.05882353 = coord(1/17)
    Abstract
    Interdisciplinary collaboration is a major goal in research policy. This study uses citation analysis to examine diverse subjects in the Web of Science and Scopus to ascertain whether, in general, research published in journals classified in more than one subject is more highly cited than research published in journals classified in a single subject. For each subject, the study divides the journals into two disjoint sets called Multi and Mono. Multi consists of all journals in the subject and at least one other subject whereas Mono consists of all journals in the subject and in no other subject. The main findings are: (a) For social science subject categories in both the Web of Science and Scopus, the average citation levels of articles in Mono and Multi are very similar; and (b) for Scopus subject categories within life sciences, health sciences, and physical sciences, the average citation level of Mono articles is roughly twice that of Multi articles. Hence, one cannot assume that in general, multidisciplinary research will be more highly cited, and the converse is probably true for many areas of science. A policy implication is that, at least in the sciences, multidisciplinary researchers should not be evaluated by citations on the same basis as monodisciplinary researchers.
  5. Kousha, K.; Thelwall, M.: Google book search : citation analysis for social science and the humanities (2009) 0.00 
    4.503549E-4 = product of:
  0.0076560336 = sum of:
    0.0076560336 = weight(_text_:in in 2946) [ClassicSimilarity], result of:
      0.0076560336 = score(doc=2946,freq=18.0), product of:
        0.033961542 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.024967048 = queryNorm
        0.22543246 = fieldWeight in 2946, product of:
          4.2426405 = tf(freq=18.0), with freq of:
            18.0 = termFreq=18.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2946)
  0.05882353 = coord(1/17)
    Abstract
    In both the social sciences and the humanities, books and monographs play significant roles in research communication. The absence of citations from most books and monographs from the Thomson Reuters/Institute for Scientific Information databases (ISI) has been criticized, but attempts to include citations from or to books in the research evaluation of the social sciences and humanities have not led to widespread adoption. This article assesses whether Google Book Search (GBS) can partially fill this gap by comparing citations from books with citations from journal articles to journal articles in 10 science, social science, and humanities disciplines. Book citations were 31% to 212% of ISI citations and, hence, numerous enough to supplement ISI citations in the social sciences and humanities covered, but not in the sciences (3%-5%), except for computing (46%), due to numerous published conference proceedings. A case study was also made of all 1,923 articles in the 51 information science and library science ISI-indexed journals published in 2003. Within this set, highly book-cited articles tended to receive many ISI citations, indicating a significant relationship between the two types of citation data, but with important exceptions that point to the additional information provided by book citations. In summary, GBS is clearly a valuable new source of citation data for the social sciences and humanities. One practical implication is that book-oriented scholars should consult it for additional citations to their work when applying for promotion and tenure.
  6. Thelwall, M.: ¬A layered approach for investigating the topological structure of communities in the Web (2003) 0.00 
    4.245987E-4 = product of:
  0.007218178 = sum of:
    0.007218178 = weight(_text_:in in 4450) [ClassicSimilarity], result of:
      0.007218178 = score(doc=4450,freq=16.0), product of:
        0.033961542 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.024967048 = queryNorm
        0.21253976 = fieldWeight in 4450, product of:
          4.0 = tf(freq=16.0), with freq of:
            16.0 = termFreq=16.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4450)
  0.05882353 = coord(1/17)
    Abstract
    A layered approach for identifying communities in the Web is presented and explored by applying the flake exact community identification algorithm to the UK academic Web. Although community or topic identification is a common task in information retrieval, a new perspective is developed by: the application of alternative document models, shifting the focus from individual pages to aggregated collections based upon Web directories, domains and entire sites; the removal of internal site links; and the adaptation of a new fast algorithm to allow fully-automated community identification using all possible single starting points. The overall topology of the graphs in the three least-aggregated layers was first investigated and found to include a large number of isolated points but, surprisingly, with most of the remainder being in one huge connected component, exact proportions varying by layer. The community identification process then found that the number of communities far exceeded the number of topological components, indicating that community identification is a potentially useful technique, even with random starting points. Both the number and size of communities identified was dependent on the parameter of the algorithm, with very different results being obtained in each case. In conclusion, the UK academic Web is embedded with layers of non-trivial communities and, if it is not unique in this, then there is the promise of improved results for information retrieval algorithms that can exploit this additional structure, and the application of the technique directly to partially automate Web metrics tasks such as that of finding all pages related to a given subject hosted by a single country's universities.
  7. Thelwall, M.; Kousha, K.: Online presentations as a source of scientific impact? : an analysis of PowerPoint files citing academic journals (2008) 0.00 
    4.245987E-4 = product of:
  0.007218178 = sum of:
    0.007218178 = weight(_text_:in in 1614) [ClassicSimilarity], result of:
      0.007218178 = score(doc=1614,freq=16.0), product of:
        0.033961542 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.024967048 = queryNorm
        0.21253976 = fieldWeight in 1614, product of:
          4.0 = tf(freq=16.0), with freq of:
            16.0 = termFreq=16.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1614)
  0.05882353 = coord(1/17)
    Abstract
    Open-access online publication has made available an increasingly wide range of document types for scientometric analysis. In this article, we focus on citations in online presentations, seeking evidence of their value as nontraditional indicators of research impact. For this purpose, we searched for online PowerPoint files mentioning any one of 1,807 ISI-indexed journals in ten science and ten social science disciplines. We also manually classified 1,378 online PowerPoint citations to journals in eight additional science and social science disciplines. The results showed that very few journals were cited frequently enough in online PowerPoint files to make impact assessment worthwhile, with the main exceptions being popular magazines like Scientific American and Harvard Business Review. Surprisingly, however, there was little difference overall in the number of PowerPoint citations to science and to the social sciences, and also in the proportion representing traditional impact (about 60%) and wider impact (about 15%). It seems that the main scientometric value for online presentations may be in tracking the popularization of research, or for comparing the impact of whole journals rather than individual articles.
  8. Thelwall, M.; Wilkinson, D.: Finding similar academic Web sites with links, bibliometric couplings and colinks (2004) 0.00 
    4.0280976E-4 = product of:
  0.0068477658 = sum of:
    0.0068477658 = weight(_text_:in in 2571) [ClassicSimilarity], result of:
      0.0068477658 = score(doc=2571,freq=10.0), product of:
        0.033961542 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.024967048 = queryNorm
        0.20163295 = fieldWeight in 2571, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=2571)
  0.05882353 = coord(1/17)
    Abstract
    A common task in both Webmetrics and Web information retrieval is to identify a set of Web pages or sites that are similar in content. In this paper we assess the extent to which links, colinks and couplings can be used to identify similar Web sites. As an experiment, a random sample of 500 pairs of domains from the UK academic Web were taken and human assessments of site similarity, based upon content type, were compared against ratings for the three concepts. The results show that using a combination of all three gives the highest probability of identifying similar sites, but surprisingly this was only a marginal improvement over using links alone. Another unexpected result was that high values for either colink counts or couplings were associated with only a small increased likelihood of similarity. The principal advantage of using couplings and colinks was found to be greater coverage in terms of a much larger number of pairs of sites being connected by these measures, instead of increased probability of similarity. In information retrieval terminology, this is improved recall rather than improved precision.
  9. Thelwall, M.: Quantitative comparisons of search engine results (2008) 0.00 
    3.6771328E-4 = product of:
  0.0062511256 = sum of:
    0.0062511256 = weight(_text_:in in 2350) [ClassicSimilarity], result of:
      0.0062511256 = score(doc=2350,freq=12.0), product of:
        0.033961542 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.024967048 = queryNorm
        0.18406484 = fieldWeight in 2350, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2350)
  0.05882353 = coord(1/17)
    Abstract
    Search engines are normally used to find information or Web sites, but Webometric investigations use them for quantitative data such as the number of pages matching a query and the international spread of those pages. For this type of application, the accuracy of the hit count estimates and range of URLs in the full results are important. Here, we compare the applications programming interfaces of Google, Yahoo!, and Live Search for 1,587 single word searches. The hit count estimates were broadly consistent but with Yahoo! and Google, reporting 5-6 times more hits than Live Search. Yahoo! tended to return slightly more matching URLs than Google, with Live Search returning significantly fewer. Yahoo!'s result URLs included a significantly wider range of domains and sites than the other two, and there was little consistency between the three engines in the number of different domains. In contrast, the three engines were reasonably consistent in the number of different top-level domains represented in the result URLs, although Yahoo! tended to return the most. In conclusion, quantitative results from the three search engines are mostly consistent but with unexpected types of inconsistency that users should be aware of. Google is recommended for hit count estimates but Yahoo! is recommended for all other Webometric purposes.
  10. Thelwall, M.: Bibliometrics to webometrics (2009) 0.00 
    3.640176E-4 = product of:
  0.006188299 = sum of:
    0.006188299 = weight(_text_:in in 4239) [ClassicSimilarity], result of:
      0.006188299 = score(doc=4239,freq=6.0), product of:
        0.033961542 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.024967048 = queryNorm
        0.1822149 = fieldWeight in 4239, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0546875 = fieldNorm(doc=4239)
  0.05882353 = coord(1/17)
    Abstract
    Bibliometrics has changed out of all recognition since 1958; becoming established as a field, being taught widely in library and information science schools, and being at the core of a number of science evaluation research groups around the world. This was all made possible by the work of Eugene Garfield and his Science Citation Index. This article reviews the distance that bibliometrics has travelled since 1958 by comparing early bibliometrics with current practice, and by giving an overview of a range of recent developments, such as patent analysis, national research evaluation exercises, visualization techniques, new applications, online citation indexes, and the creation of digital libraries. Webometrics, a modern, fast-growing offshoot of bibliometrics, is reviewed in detail. Finally, future prospects are discussed with regard to both bibliometrics and webometrics.
    Source
    Information science in transition, Ed.: A. Gilchrist
  11. Thelwall, M.: Webometrics (2009) 0.00 
    3.6028394E-4 = product of:
  0.006124827 = sum of:
    0.006124827 = weight(_text_:in in 3906) [ClassicSimilarity], result of:
      0.006124827 = score(doc=3906,freq=8.0), product of:
        0.033961542 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.024967048 = queryNorm
        0.18034597 = fieldWeight in 3906, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=3906)
  0.05882353 = coord(1/17)
    Abstract
    Webometrics is an information science field concerned with measuring aspects of the World Wide Web (WWW) for a variety of information science research goals. It came into existence about five years after the Web was formed and has since grown to become a significant aspect of information science, at least in terms of published research. Although some webometrics research has focused on the structure or evolution of the Web itself or the performance of commercial search engines, most has used data from the Web to shed light on information provision or online communication in various contexts. Most prominently, techniques have been developed to track, map, and assess Web-based informal scholarly communication, for example, in terms of the hyperlinks between academic Web sites or the online impact of digital repositories. In addition, a range of nonacademic issues and groups of Web users have also been analyzed.
  12. Thelwall, M.: Extracting macroscopic information from Web links (2001) 0.00 
    3.3567476E-4 = product of:
  0.005706471 = sum of:
    0.005706471 = weight(_text_:in in 6851) [ClassicSimilarity], result of:
      0.005706471 = score(doc=6851,freq=10.0), product of:
        0.033961542 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.024967048 = queryNorm
        0.16802745 = fieldWeight in 6851, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=6851)
  0.05882353 = coord(1/17)
    Abstract
    Much has been written about the potential and pitfalls of macroscopic Web-based link analysis, yet there have been no studies that have provided clear statistical evidence that any of the proposed calculations can produce results over large areas of the Web that correlate with phenomena external to the Internet. This article attempts to provide such evidence through an evaluation of Ingwersen's (1998) proposed external Web Impact Factor (WIF) for the original use of the Web: the interlinking of academic research. In particular, it studies the case of the relationship between academic hyperlinks and research activity for universities in Britain, a country chosen for its variety of institutions and the existence of an official government rating exercise for research. After reviewing the numerous reasons why link counts may be unreliable, it demonstrates that four different WIFs do, in fact, correlate with the conventional academic research measures. The WIF delivering the greatest correlation with research rankings was the ratio of Web pages with links pointing at research-based pages to faculty numbers. The scarcity of links to electronic academic papers in the data set suggests that, in contrast to citation analysis, this WIF is measuring the reputations of universities and their scholars, rather than the quality of their publications
  13. Thelwall, M.: Interpreting social science link analysis research : a theoretical framework (2006) 0.00 
    3.1201506E-4 = product of:
  0.005304256 = sum of:
    0.005304256 = weight(_text_:in in 4908) [ClassicSimilarity], result of:
      0.005304256 = score(doc=4908,freq=6.0), product of:
        0.033961542 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.024967048 = queryNorm
        0.1561842 = fieldWeight in 4908, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=4908)
  0.05882353 = coord(1/17)
    Abstract
    Link analysis in various forms is now an established technique in many different subjects, reflecting the perceived importance of links and of the Web. A critical but very difficult issue is how to interpret the results of social science link analyses. lt is argued that the dynamic nature of the Web, its lack of quality control, and the online proliferation of copying and imitation mean that methodologies operating within a highly positivist, quantitative framework are ineffective. Conversely, the sheer variety of the Web makes application of qualitative methodologies and pure reason very problematic to large-scale studies. Methodology triangulation is consequently advocated, in combination with a warning that the Web is incapable of giving definitive answers to large-scale link analysis research questions concerning social factors underlying link creation. Finally, it is claimed that although theoretical frameworks are appropriate for guiding research, a Theory of Link Analysis is not possible.
  14. Payne, N.; Thelwall, M.: Mathematical models for academic webs : linear relationship or non-linear power law? (2005) 0.00 
    2.972191E-4 = product of:
  0.005052725 = sum of:
    0.005052725 = weight(_text_:in in 1066) [ClassicSimilarity], result of:
      0.005052725 = score(doc=1066,freq=4.0), product of:
        0.033961542 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.024967048 = queryNorm
        0.14877784 = fieldWeight in 1066, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0546875 = fieldNorm(doc=1066)
  0.05882353 = coord(1/17)
    Abstract
    Previous studies of academic web interlinking have tended to hypothesise that the relationship between the research of a university and links to or from its web site should follow a linear trend, yet the typical distribution of web data, in general, seems to be a non-linear power law. This paper assesses whether a linear trend or a power law is the most appropriate method with which to model the relationship between research and web site size or outlinks. Following linear regression, analysis of the confidence intervals for the logarithmic graphs, and analysis of the outliers, the results suggest that a linear trend is more appropriate than a non-linear power law.
    Footnote
    Beitrag in einem "Special Issue on Infometrics"
  15. Thelwall, M.; Vaughan, L.; Björneborn, L.: Webometrics (2004) 0.00 
    2.6001257E-4 = product of:
  0.004420214 = sum of:
    0.004420214 = weight(_text_:in in 4279) [ClassicSimilarity], result of:
      0.004420214 = score(doc=4279,freq=6.0), product of:
        0.033961542 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.024967048 = queryNorm
        0.1301535 = fieldWeight in 4279, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4279)
  0.05882353 = coord(1/17)
    Abstract
    Webometrics, the quantitative study of Web-related phenomena, emerged from the realization that methods originally designed for bibliometric analysis of scientific journal article citation patterns could be applied to the Web, with commercial search engines providing the raw data. Almind and Ingwersen (1997) defined the field and gave it its name. Other pioneers included Rodriguez Gairin (1997) and Aguillo (1998). Larson (1996) undertook exploratory link structure analysis, as did Rousseau (1997). Webometrics encompasses research from fields beyond information science such as communication studies, statistical physics, and computer science. In this review we concentrate on link analysis, but also cover other aspects of webometrics, including Web log fle analysis. One theme that runs through this chapter is the messiness of Web data and the need for data cleansing heuristics. The uncontrolled Web creates numerous problems in the interpretation of results, for instance, from the automatic creation or replication of links. The loose connection between top-level domain specifications (e.g., com, edu, and org) and their actual content is also a frustrating problem. For example, many .com sites contain noncommercial content, although com is ostensibly the main commercial top-level domain. Indeed, a skeptical researcher could claim that obstacles of this kind are so great that all Web analyses lack value. As will be seen, one response to this view, a view shared by critics of evaluative bibliometrics, is to demonstrate that Web data correlate significantly with some non-Web data in order to prove that the Web data are not wholly random. A practical response has been to develop increasingly sophisticated data cleansing techniques and multiple data analysis methods.
  16. Kousha, K.; Thelwall, M.: Google Scholar citations and Google Web/URL citations : a multi-discipline exploratory analysis (2007) 0.00 
    2.6001257E-4 = product of:
  0.004420214 = sum of:
    0.004420214 = weight(_text_:in in 337) [ClassicSimilarity], result of:
      0.004420214 = score(doc=337,freq=6.0), product of:
        0.033961542 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.024967048 = queryNorm
        0.1301535 = fieldWeight in 337, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=337)
  0.05882353 = coord(1/17)
    Abstract
    We use a new data gathering method, "Web/URL citation," Web/URL and Google Scholar to compare traditional and Web-based citation patterns across multiple disciplines (biology, chemistry, physics, computing, sociology, economics, psychology, and education) based upon a sample of 1,650 articles from 108 open access (OA) journals published in 2001. A Web/URL citation of an online journal article is a Web mention of its title, URL, or both. For each discipline, except psychology, we found significant correlations between Thomson Scientific (formerly Thomson ISI, here: ISI) citations and both Google Scholar and Google Web/URL citations. Google Scholar citations correlated more highly with ISI citations than did Google Web/URL citations, indicating that the Web/URL method measures a broader type of citation phenomenon. Google Scholar citations were more numerous than ISI citations in computer science and the four social science disciplines, suggesting that Google Scholar is more comprehensive for social sciences and perhaps also when conference articles are valued and published online. We also found large disciplinary differences in the percentage overlap between ISI and Google Scholar citation sources. Finally, although we found many significant trends, there were also numerous exceptions, suggesting that replacing traditional citation sources with the Web or Google Scholar for research impact calculations would be problematic.
  17. Thelwall, M.: ¬A comparison of sources of links for academic Web impact factor calculations (2002) 0.00 
    2.5475924E-4 = product of:
  0.004330907 = sum of:
    0.004330907 = weight(_text_:in in 4474) [ClassicSimilarity], result of:
      0.004330907 = score(doc=4474,freq=4.0), product of:
        0.033961542 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.024967048 = queryNorm
        0.12752387 = fieldWeight in 4474, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=4474)
  0.05882353 = coord(1/17)
    Abstract
    There has been much recent interest in extracting information from collections of Web links. One tool that has been used is Ingwersen's Web impact factor. It has been demonstrated that several versions of this metric can produce results that correlate with research ratings of British universities showing that, despite being a measure of a purely Internet phenomenon, the results are susceptible to a wider interpretation. This paper addresses the question of which is the best possible domain to count backlinks from, if research is the focus of interest. WIFs for British universities calculated from several different source domains are compared, primarily the .edu, .ac.uk and .uk domains, and the entire Web. The results show that all four areas produce WIFs that correlate strongly with research ratings, but that none produce incontestably superior figures. It was also found that the WIF was less able to differentiate in more homogeneous subsets of universities, although positive results are still possible.
  18. Thelwall, M.: Web impact factors and search engine coverage (2000) 0.00 
    2.401893E-4 = product of:
  0.004083218 = sum of:
    0.004083218 = weight(_text_:in in 4539) [ClassicSimilarity], result of:
      0.004083218 = score(doc=4539,freq=2.0), product of:
        0.033961542 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.024967048 = queryNorm
        0.120230645 = fieldWeight in 4539, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0625 = fieldNorm(doc=4539)
  0.05882353 = coord(1/17)
    Abstract
    Search engines index only a proportion of the web and this proportion is not determined randomly but by following algorithms that take into account the properties that impact factors measure. A survey was conducted in order to test the coverage of search engines and to decide thether their partial coverage is indeed an obstacle to using them to calculate web impact factors. The results indicate that search engine coverage, even of large national domains is extremely uneven and would be likely to lead to misleading calculations
  19. Barjak, F.; Li, X.; Thelwall, M.: Which factors explain the Web impact of scientists' personal homepages? (2007) 0.00 
    2.401893E-4 = product of:
  0.004083218 = sum of:
    0.004083218 = weight(_text_:in in 73) [ClassicSimilarity], result of:
      0.004083218 = score(doc=73,freq=8.0), product of:
        0.033961542 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.024967048 = queryNorm
        0.120230645 = fieldWeight in 73, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.03125 = fieldNorm(doc=73)
  0.05882353 = coord(1/17)
    Abstract
    In recent years, a considerable body of Webometric research has used hyperlinks to generate indicators for the impact of Web documents and the organizations that created them. The relationship between this Web impact and other, offline impact indicators has been explored for entire universities, departments, countries, and scientific journals, but not yet for individual scientists-an important omission. The present research closes this gap by investigating factors that may influence the Web impact (i.e., inlink counts) of scientists' personal homepages. Data concerning 456 scientists from five scientific disciplines in six European countries were analyzed, showing that both homepage content and personal and institutional characteristics of the homepage owners had significant relationships with inlink counts. A multivariate statistical analysis confirmed that full-text articles are the most linked-to content in homepages. At the individual homepage level, hyperlinks are related to several offline characteristics. Notable differences regarding total inlinks to scientists' homepages exist between the scientific disciplines and the countries in the sample. There also are both gender and age effects: fewer external inlinks (i.e., links from other Web domains) to the homepages of female and of older scientists. There is only a weak relationship between a scientist's recognition and homepage inlinks and, surprisingly, no relationship between research productivity and inlink counts. Contrary to expectations, the size of collaboration networks is negatively related to hyperlink counts. Some of the relationships between hyperlinks to homepages and the properties of their owners can be explained by the content that the homepage owners put on their homepage and their level of Internet use; however, the findings about productivity and collaborations do not seem to have a simple, intuitive explanation. Overall, the results emphasize the complexity of the phenomenon of Web linking, when analyzed at the level of individual pages.
  20. Vaughan, L.; Thelwall, M.: Scholarly use of the Web : what are the key inducers of links to journal Web sites? (2003) 0.00 
    2.1229935E-4 = product of:
  0.003609089 = sum of:
    0.003609089 = weight(_text_:in in 1236) [ClassicSimilarity], result of:
      0.003609089 = score(doc=1236,freq=4.0), product of:
        0.033961542 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.024967048 = queryNorm
        0.10626988 = fieldWeight in 1236, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1236)
  0.05882353 = coord(1/17)
    Abstract
    Web links have been studied by information scientists for at least six years but it is only in the past two that clear evidence has emerged to show that counts of links to scholarly Web spaces (universities and departments) can correlate significantly with research measures, giving some credence to their use for the investigation of scholarly communication. This paper reports an a study to investigate the factors that influence the creation of links to journal Web sites. An empirical approach is used: collecting data and testing for significant patterns. The specific questions addressed are whether site age and site content are inducers of links to a journal's Web site as measured by the ratio of link counts to Journal Impact Factors, two variables previously discovered to be related. A new methodology for data collection is also introduced that uses the Internet Archive to obtain an earliest known creation date for Web sites. The results show that both site age and site content are significant factors for the disciplines studied: library and information science, and law. Comparisons between the two fields also show disciplinary differences in Web site characteristics. Scholars and publishers should be particularly aware that richer content an a journal's Web site tends to generate links and thus the traffic to the site.

Authors

Languages

  • e 23
  • d 1
  • More… Less…

Themes