Identifying emergent behaviours from longitudinal web use

Abstract

Laboratory studies present difficulties in the understanding of how usage evolves over time. Employed observations are obtrusive and not naturalistic. Our system employs a remote capture tool that provides longitudinal low-level interaction data. It is easily deployable into any Web site allowing deployments in-the-wild and is completely unobtrusive. Web application interfaces are designed assuming users' goals. Requirement specifications contain well defined use cases and scenarios that drive design and subsequent optimisations. Users' interaction patterns outside the expected ones are not considered. This results in an optimisation for a stylised user rather than a real one. A bottom-up analysis from low-level interaction data makes possible the emergence of users' tasks. Similarities among users can be found and solutions that are effective for real users can be designed. Factors such as learnability and how interface changes affect users are difficult to observe in laboratory studies. Our solution makes it possible, adding a longitudinal point of view to traditional laboratory studies. The capture tool is deployed in real world Web applications capturing in-situ data from users. These data serve to explore analysis and visualisation possibilities. We present an example of the exploration results with one Web application.