Usage of different Web Impact Factors for Ranking Australian Universities*
BibTeX
@MISC{Boell_usageof,
author = {Sebastian K. Boell and Concepción S. Wilson and Fletcher T. H. Cole},
title = {Usage of different Web Impact Factors for Ranking Australian Universities*},
year = {}
}
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Abstract
This study describes how search engines (SE) can be employed for automated, efficient data gathering for Webometric studies using well defined query specfic URLs in SE (predictable URLs). It then compares the usage of staff-related Web Impact Factors (WIFs) to web impact factors for a ranking of Australian universities, showing that rankings based on staff-related WIFs correlate much better with an established ranking from the Melbourne Institute than commonly used WIFs. In fact WIFs do not correlate with the Melbourne ranking at all. It also compares WIF data for Australian Universities provided by Smith [1] for a longitudinal comparison of the WIF of Australian Universities over the last decade. It shows that size-dependent WIF values declined for most Australian universities over the last ten years, while staffdependent WIFs shows a riding trend. 1.
