Recommender systems effect on user' choice behaviour

Recommender systems (RSs) research is so far focused mainly on improving recommendations' quality and precision. However, it is also important to discover the effect of RSs on users' behaviours. So far, very few researches have analysed the effect of RSs on users' behaviours. Therefore, not much knowledge about this essential topic is obtained. Hence, in this PhD researchwe focus on RSs' effect on users' behaviours. In order to investigate this effect, we propose a simulation procedure of users' choices under the influence of a RS. Then we measure metrics on users' choices that capture RSs effect. Moreover, we propose to conduct online experiments to study the effect of RSs by designing web-based platforms tracking the choices of the users in systems that offer also recommendations to the users.