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Wolverhampton Intellectual Repository and E-Theses > School of Technology > School of Computing and IT > Statistical Cybermetrics Research Group  > An initial exploration of the link relationship between UK university Web sites.

Please use this identifier to cite or link to this item: http://hdl.handle.net/2436/4016
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Title: An initial exploration of the link relationship between UK university Web sites.
Authors: Thelwall, Mike
Citation: Aslib Proceedings, 54(2): 118-128
Publisher: MCB UP Ltd
Issue Date: 2002
URI: http://hdl.handle.net/2436/4016
DOI: 10.1108/00012530210435248
Additional Links: http://www.emeraldinsight.com/10.1108/00012530210435248
Abstract: Aggregates of links are of interest to information scientists in the same way as citation counts are: as potential sources of data from which new knowledge can be mined. Builds on the recent discovery of a correlation between a Web link count measure and the research quality of British universities by applying a range of multivariate statistical techniques to counts of links between pairs of universities. This represents an initial attempt at developing an understanding of this phenomenon. Extracts plausible results. Also identifies outliers in the data by the techniques, some of which were verified by being tracked down to identifiable Web phenomena. This is an important outcome because successful anomaly identification is a precondition to more effective analysis of this kind of data. The identification of groupings is encouraging evidence that Web links between universities can be mined for significant results, although it is clear that more methodological development is needed, if any but the simplest patterns are to be extracted. Finally, based upon the types of patterns extracted, argues that none of the methods used are capable of fully analysing link structures on their own.
Type: Article
Language: en
Keywords: Internet
Universities
User studies
Networks
Weblinks
Academic websites
ISSN: 0001253X
Appears in Collections: Statistical Cybermetrics Research Group
Statistical Cybermetrics Research Group

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