Associated with the Linz Institute of Technology and the Institute of Computational Perception @ JKU Linz, Austria

The Importance of Cognitive Biases in the Recommendation Ecosystem: Evidence of Feature-Positive Effect, Ikea Effect, and Cultural Homophily

Abstract

Cognitive biases have been studied in psychology, sociology, and behavioral economics for decades. Traditionally, they have been considered a negative human trait that leads to inferior decision making, reinforcement ofstereotypes, or can be exploited to manipulate consumers, respectively. Lately, there has been growing interest inAI research to better understand the influence of such biases in classification, search, and also recommendation tasks. We argue that cognitive biases manifest in different parts of the recommendation ecosystem and in various components of the recommendation pipeline, including input data (such as ratings or side information), recommendation algorithm or model (and consequently recommended items), and user interactions with the system. More importantly, we contest the traditional detrimental perspective on cognitive biases and claim that certain cognitive biases can be beneficial when accounted for by recommender systems. Concretely, we provide empirical evidence that feature-positive effect, Ikea effect, and cultural homophily can be observed in the context of recommender systems, and discuss their potential for exploitation. In three small experiments covering recruitment and entertainment domains, we study the pervasiveness of the aforementioned biases. We ultimately advocate for a prejudice-free consideration of cognitive biases to improve user and item models as well as recommendation algorithms.


Citation

Oleg Lesota, Shahed Masoudian, Markus Schedl
The Importance of Cognitive Biases in the Recommendation Ecosystem: Evidence of Feature-Positive Effect, Ikea Effect, and Cultural Homophily
Proceedings of the 11th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems co-located with 18th ACM Conference on Recommender Systems (RecSys 2024), 2024.

BibTeX

@article{Lesota2024CogBias,
    title = {The Importance of Cognitive Biases in the Recommendation Ecosystem: Evidence of Feature-Positive Effect, Ikea Effect, and Cultural Homophily},
    author = {Lesota, Oleg and Masoudian, Shahed and Schedl, Markus},
    booktitle = {Proceedings of the 11th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems co-located with 18th ACM Conference on Recommender Systems (RecSys 2024)},
    publisher = {CEUR-WS.org},
    url = {https://ceur-ws.org/Vol-3815/paper10.pdf},
    year = {2024}
}

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