Abstract
Psychological processes play a critical role in shaping users' interactions with information retrieval (IR) and recommender systems (RS). Therefore, understanding human cognition, decision-making, and emotions is vital to enable user-centric retrieval and recommendation systems. Vice versa, understanding whether these aspects are also present in the systems themselves (e.g., in training data, ranking models, or outputs), or even injecting them on purpose, can inform the development of psychology-inspired systems. The purpose of this tutorial is to provide its attendees with an introduction to psychological concepts that are important in the ecosystem of search, retrieval, and recommendation, in particular, cognitive architectures, cognitive effects and biases, as well as personality and affect. Leveraging corresponding models allows its audience to build or refine psychology-informed IR and RS technology. The interdisciplinary tutorial requires intermediate expertise in terms of IR and RS, while we do not assume knowledge in psychology.
Citation
Markus
Schedl,
Elisabeth Lex,
Marko Tkalcic
Psychological Aspects in Retrieval and Recommendation
SIGIR '25: Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025.
BibTeX
@inproceedings{Schedl2025PsyAsp,
title = {Psychological Aspects in Retrieval and Recommendation},
author = {Schedl, Markus and Elisabeth Lex and Marko Tkalcic},
booktitle = {SIGIR '25: Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval},
year = {2025}
}