Methods for reporting on the targets of links from national systems of university Web sites

Abstract

Whilst hyperlinks within Web sites may be primarily created for navigation purposes, those between sites are a rich source of information about the content and use of the Web. As a result there is a need to derive descriptive statistics about them, both to help understand the underlying communication processes and so that policy makers can gain insights into the use of online information by those located within their constituency. It is known, however, that using the individual web link source page as the basic unit of counting is problematical because of the number and size of link anomalies. The challenge addressed in this paper is that of developing methods to assess techniques for counting links from groups of large university web sites (site outlinks). Two methods to assess the reliability of link counts are developed and applied to judge which of seven advanced document models are most appropriate in each case. The most generally applicable method used is an internal consistency test based upon a highly simplified model of web linking behaviour. The data used comes from crawls of UK, Australian and New Zealand universities. The standard domain advanced web document model emerges as the logical choice for comparison purposes within this set. Some descriptive statistics concerning Top Level Domain link targets are given and it is demonstrated that the choice of model can effect the final results.

Hyperlinks and networked communication: a comparative study of political parties online

“…8 See Thelwall (2002Thelwall ( , 2004 for more on aggregating pages into groups or clusters using alternative document models (ADMs) based upon directories, domains and multi-domain sites. 9 For example, there are 136 pages that are hosted by the commercial free web hosting service www.geocities.com and these have been aggregated into a single network node even though these pages are from a large number of diverse and unrelated websites.…”

A comparison of methods for collecting web citation data for academic organizations

“…A variant of link counting, Google's PageRank (Brin & Page, 1998), has been a high profile endorsement that links indicate impact but a number of articles have also explicitly tested this. In particular, counts of inlinks (i.e., hyperlinks originating in other websites, sometimes called site inlinks [Björneborn & Ingwersen, 2004]) to university websites correlate with research productivity for the UK (Thelwall & Harries, 2004), Australia (Thelwall, 2004), and New Zealand (Thelwall, 2004), and the same is true for some disciplines in the UK (Li, Thelwall, Wilkinson, & Musgrove, 2005a). More directly, counts of links to journal websites correlate with journal Impact Factors Vaughan & Hysen, 2002) for homogenous journal sets but numbers of links pointing to a research website are not a good indicator of researcher productivity (Barjak et al, 2007).…”

Digital libraries

“…For example, Australian researchers asked whether clinicians' use of a database created for them was related to their care of patients (Westbrook, Gosling, & Coiera, 2004). Following backlinks to identify the sources that referred users to a digital library (and even what they were seeking at those sites) can provide insight into what user needs are being served by the digital library (Thelwall, 2004). Query term analysis and content analysis of comments and full‐text questions presumably addressed to a reference librarian can help a digital library service identify not only the topics in which its users are interested but also the kinds of ancillary data that they expect to find in conjunction with their searches.…”