Abstract
Recommender Systems (RS) have become indispensable tools to support users when confronted with large collections. They focus the attention of users on a subset of items out of a variety of choices. Therefore RS are inherently persuasive online tools trying to pair users with items that might constitute a better match with their preferences than those choices the users might know already or they could detect on their own without the help of virtual guides. The goal of this talk is therefore to explore the range of influential cues and aspects that have been shown to influence the opinions of users and discuss avenues for further research.