Abstract not found

models for counting links between university web sites

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 homogenous subsets of universities, although positive results are still possible.

Three new metrics are introduced that measure the range of use of a university Web site by its peers through different heuristics for counting links targeted at its pages. All three give results that correlate significantly with the research productivity of the target institution. The directory range model, which is based upon summing the number of distinct directories targeted by each other university, produces the most promising results of any link metric yet. Based upon an analysis of changes between models, it is suggested that range models measure essentially the same quantity as their predecessors but are less susceptible to spurious causes of multiple links and are therefore more robust.

There have been many attempts to study the content of the web, either through human or automatic agents. Five different previously used web survey methodologies are described and analysed, each justifiable in its own right, but a simple experiment is presented that demonstrates concrete differences between them. The concept of crawling the web also bears further inspection, including the scope of the pages to crawl, the method used to access and index each page, and the algorithm for the identification of duplicate pages. The issues involved here will be well-known to many computer scientists but, with the increasing use of crawlers and search engines in other disciplines, they now require a public discussion in the wider research community. This paper concludes that any scientific attempt to crawl the web must make available the parameters under which it is operating so that researchers can, in principle, replicate experiments or be aware of and take into account differences between methodologies. A new hybrid random page selection methodology is also introduced.

This paper uses a page categorization in order to show that restricting the metrics to subsets more closely related to the research of the host university can produce even stronger associations. A partial overlap was also found between the effects of applying advanced document models and separating page types, but the best results were achieved through a combination of the two

Web links are a phenomenon of interest to bibliometricians by analogy with citations, and to others because of their use in web navigation and search engines. It is known that very few links on university web sites are targeted at scholarly expositions and yet, at least in the UK and Australia, a correlation has been established between link count metrics for universities and measures of institutional research. This paper operates on a finer-grained level of detail, focussing on counts of links between pairs of universities. It provides evidence of an underlying linear relationship with the quadruple product of the size and research quality of both source and target institution. This simple model is proposed as applying generally to national university systems, subject to a series of constraints to identify cases where it is unlikely to be applicable. It is hoped that the model, if confirmed by studies of other countries, will open the door to deeper mining of academic web link data.

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. The recent discovery of a correlation between a web link count measure and the research quality of British universities is built upon 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. Plausible results are extracted, including the high degree of similarity between the Scottish universities and limited evidence of a dichotomy between new and traditional universities. Outliers in the data were also identified 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 it is argued that none of the methods used are capable of fully analysing link structures on their own.

Purpose – We analyse the link-based web site impact measure known as the Web Impact Factor (WIF). It is a quantitative tool for evaluating and ranking web sites, top-level domains and sub-domains. We also discuss the WIF's advantages and disadvantages, data collection problems, and validity and reliability of WIF results. Design/methodology/approach – A key to webometric studies has been the use of largescale search engines, such as Yahoo and AltaVista that allow measurements to be made of the total number of pages in a web site and the total number of backlinks to the web site. These search engines provide similar possibilities for the investigation of links between web sites/pages to those provided by the academic journals citation databases from the Institute of Scientific Information (ISI). But the content of the Web is not of the same nature and quality as the databases maintained by the ISI. Findings – This paper reviews how the WIF has been developed and applied. It has been suggested that Web Impact Factors can be calculated as a way of comparing the attractiveness of web sites or domains on the Web. It is concluded that, while the WIF is arguably useful for quantitative intra-country comparison, application beyond this (i.e., to inter-country assessment) has little value. Originality/value – The paper attempts to make a critical review over literature on the WIF and associated indicators.

A publicly accessible database of UK university website links and a discussion of the need for