A survey of Web metrics

Abstract

The unabated growth and increasing significance of the World Wide Web has resulted in a flurry of research activity to improve its capacity for serving information more effectively. But at the heart of these efforts lie implicit assumptions about "quality" and "usefulness" of Web resources and services. This observation points towards measurements and models that quantify various attributes of web sites. The science of measuring all aspects of information, especially its storage and retrieval or informetrics has interested information scientists for decades before the existence of the Web. Is Web informetrics any different, or is it just an application of classical informetrics to a new medium? In this article, we examine this issue by classifying and discussing a wide ranging set of Web metrics. We present the origins, measurement functions, formulations and comparisons of well-known Web metrics for quantifying Web graph properties , Web page significance , Web page similarity , search and retrieval , usage characterization and information theoretic properties . We also discuss how these metrics can be applied for improving Web information access and use.

The effects of online social media on tourism websites

“…This follows the proposals of the Web Analytics Association (WAA, 2008). Although not particularly meaningful per se, for the arbitrarity in the definition, when measured consistently over a period of time, visits are a good indicator of the behaviour of website with respect to its popularity (Dhyani et al, 2002;Polanco, 2003).…”

Web graph similarity for anomaly detection

“…A slight variation on this approach is proposed by [19], which computes the similarity of vertex degree distributions. We believe this variation can readily be extended to other graph properties such as those discussed in [10]. Similarly, if one has edge properties, it is possible to construct edge vectors and compare them.…”

Toward an analytical approach for effective Web site design: A framework for modeling, evaluation and enhancement

“…Ivory and Hearst (2002) surveyed popular (automated) website evaluation methods and graphical design practices, highlighting the importance of such design elements as architecture, page, link, text and graphics. Dhyani et al (2002) classified and discussed a wide range of Web metrics and quantifies various attributes of Web sites, including Web graph properties, Web page significance (e.g. PageRank), Web page similarity, search and retrieval, usage characterization and information theoretic properties.…”