Long Tail Attributes of Knowledge Worker Intranet Interactions
Pages 419 - 433
Abstract
Elucidation of human browsing behavior in electronic spaces has been attracting substantial attention in academic and commercial spheres. We present a novel formal approach to human behavior analysis in web based environments. The framework has been applied to analyzing knowledge workers' browsing behavior on a large corporate Intranet. Analysis indicates that users form elemental and complex browsing patterns and achieve their browsing objectives via few subgoals. Knowledge workers know their targets and exhibit diminutive exploratory behavior. Significant long tail attributes have been observed in all analyzed features. A novel distribution that accurately models it has been introduced.
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Published: 18 July 2007
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