This repository contains all the material supporting the tutorial “Psychological Aspects in Retrieval and Recommendation”

Abstract

Information retrieval (IR) and recommender systems (RS) affect many aspects of our daily lives, influencing which content we are exposed to on the web or social media platforms, which products we buy, or which music we listen to. At the same time, psychological processes play a critical role in shaping users’ interactions with IR and RS. Therefore, understanding human cognition, decision-making processes, and psychological factors such as personality and emotion is vital to enable user-centric retrieval and recommendation systems. Vice versa, understanding whether these aspects are also present to some extent in the systems themselves (e.g., in training data, ranking models, or outputs), or even integrating them in the systems on purpose, can inform the development of psychology-inspired systems. Against this background, the tutorial focuses on three key psychological topics and sheds light on how they influence and manifest in the IR and RS ecosystem: cognitive architectures, cognitive effects and biases, and personality and affect.

Tutorial Materials

Organization