Real-time detection of navigation problems on the World 'Wild' Web. Issue 101 (May 2017) - Vigo, Markel; Harper, Simon
Abstract: We propose a set of algorithms to detect navigation problems in real-time. To do so, we operationalise some navigation strategies suggested by the literature and investigate the extent to which the exhibition of these strategies is an indicator of navigation problems. Our Firefox extension senses behaviour indicative of a user experiencing interaction problems. Once these problems are detected we can suggest changes to these sites, and eventually adapt the site in real time to better accommodate the user. A remote longitudinal study monitored real website user behaviour, analysing every application event on the client side both individually and in combination. The study was conducted with 34 participants over 400 days totalling 567 h of normal usage and with no task restriction. Our sensing algorithms detected 374 issues with a 85% precision for purposeful Web use, suggesting that, indeed, when users search for specific information the exhibition of these strategies indicates the presence of problems. This contribution is novel in that, as opposed to a post - hoc analysis of user interaction, real-time detection of navigation problems at the user end opens up new research avenues in the realm of adaptive interfaces and usability analysis. Abstract : Highlights: A remote longitudinal study monitored real website user behaviour. 400 cumulative person days, totalling approximately 567 h of normal usage, and with no task restriction. Sensing algorithms detected 374 problems. Precision of 85% for purposeful Web use.