Search (6 results, page 1 of 1)

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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

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Abstract

The primary webometric method for estimating the online impact of an organization is to count links to its website. Link counts have been available from commercial search engines for over a decade but this was set to end by early 2012 and so a replacement is needed. This article compares link counts to two alternative methods: URL citations and organization title mentions. New variations of these methods are also introduced. The three methods are compared against each other using Yahoo!. Two of the three methods (URL citations and organization title mentions) are also compared against each other using Bing. Evidence from a case study of 131 UK universities and 49 US Library and Information Science (LIS) departments suggests that Bing's Hit Count Estimates (HCEs) for popular title searches are not useful for webometric research but that Yahoo!'s HCEs for all three types of search and Bing's URL citation HCEs seem to be consistent. For exact URL counts the results of all three methods in Yahoo! and both methods in Bing are also consistent. Four types of accuracy factors are also introduced and defined: search engine coverage, search engine retrieval variation, search engine retrieval anomalies, and query polysemy.

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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.

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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.

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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.

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Abstract

Web impact factors, the proposed web equivalent of impact factors for journals, can be calculated by using search engines. It has been found that the results are problematic because of the variable coverage of search engines as well as their ability to give significantly different results over short periods of time. The fundamental problem is that although some search engines provide a functionality that is capable of being used for impact calculations, this is not their primary task and therefore they do not give guarantees as to performance in this respect. In this paper, a bespoke web crawler designed specifically for the calculation of reliable WIFs is presented. This crawler was used to calculate WIFs for a number of UK universities, and the results of these calculations are discussed. The principal findings were that with certain restrictions, WIFs can be calculated reliably, but do not correlate with accepted research rankings owing to the variety of material hosted on university servers. Changes to the calculations to improve the fit of the results to research rankings are proposed, but there are still inherent problems undermining the reliability of the calculation. These problems still apply if the WIF scores are taken on their own as indicators of the general impact of any area of the Internet, but with care would not apply to online journals.