Psychological Aspects in Retrieval and Recommendation

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.

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Publication Details

Published
2025-07-13
DOI
https://doi.org/10.1145/3726302.3731691
Citations
1
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
Field-Weighted Citation Impact
2.48
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article

Psychological Aspects in Retrieval and Recommendation

Elisabeth Lex, Marko Tkalčič, Markus Schedl
1 citations
Intelligent Tutoring Systems and Adaptive Learning
2.48
article

Psychological Aspects in Retrieval and Recommendation

Elisabeth Lex, Marko Tkalčič, Markus Schedl
article en
1 citations

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.

University of Primorska (SI), Johannes Kepler University of Linz (AT), Graz University of Technology (AT)
Openalex Percentile: Top 10%
Intelligent Tutoring Systems and Adaptive Learning
2.48
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