Measuring the impact of online personalisation

Abstract

Research on understanding, developing and assessing personalisation systems is spread over multiple disciplines and builds on methodologies and findings from several different research fields and traditions, such as Artificial Intelligence (AI), Machine Learning (ML), Human–Computer Interaction (HCI), and User Modelling based on (applied) social and cognitive psychology. The fields of AI and ML primarily focus on the optimisation of personalisation applications, and concentrate on creating ever more accurate algorithmic decision makers and prediction models. In the fields of HCI and Information Systems, scholars are primarily interested in the phenomena around the use and interaction with personalisation systems, while Cognitive Science (partly) delivers the theoretical underpinnings for the observed effects. The aim and contribution of this work is to put together the pieces about the impact of personalisation and recommendation systems from these different backgrounds in order to formulate a research agenda and provide a perspective on future developments.