Statistical profiles of highly-rated web sites

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Abstract
We are creating an interactive tool to help non-professional web site builders create high quality designs. We have previously reported that quantitative measures of web page structure can predict whether a site will be highly or poorly rated by experts, with accuracies ranging from 67--80%. In this paper we extend that work in several ways. First, we compute a much larger set of measures (157 versus 11), over a much larger collection of pages (5300 vs. 1900), achieving much higher overall accuracy (94% on average) when contrasting good, average, and poor pages. Second, we introduce new classes of measures that can make assessments at the site level and according to page type (home page, content page, etc.). Finally, we create statistical profiles of good sites, and apply them to an existing design, showing how that design can be changed to better match high-quality designs

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