Aridor, Guy;
Goncalves, Duarte;
Kong, Ruoyan;
Kluver, Daniel;
Konstan, Joseph;
(2024)
The MovieLens Beliefs Dataset: Collecting Pre-Choice Data for Online Recommender Systems.
In:
RecSys '24: Proceedings of the 18th ACM Conference on Recommender Systems.
ACM: Bari, Italy.
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Abstract
An increasingly important aspect of designing recommender systems involves considering how recommendations will influence consumer choices. This paper addresses this issue by introducing a method for collecting user beliefs about un-experienced goods – a critical predictor of choice behavior. We implemented this method on the MovieLens platform, resulting in a rich dataset that combines user ratings, beliefs, and observed recommendations. We document challenges to such data collection, including selection bias in response and limited coverage of the product space. This unique resource empowers researchers to delve deeper into user behavior and analyze user choices absent recommendations, measure the effectiveness of recommendations, and prototype algorithms that leverage user belief data, ultimately leading to more impactful recommender systems. The dataset can be found at https://grouplens.org/datasets/movielens/ml_belief_2024/.
| Type: | Proceedings paper |
|---|---|
| Title: | The MovieLens Beliefs Dataset: Collecting Pre-Choice Data for Online Recommender Systems |
| Event: | RecSys '24: 18th ACM Conference on Recommender Systems |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3640457.3688158 |
| Publisher version: | https://doi.org/10.1145/3640457.3688158 |
| Language: | English |
| Additional information: | Copyright © 2024 Owner/Author. This work is licensed under a Creative Commons Attribution International 4.0 License. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL SLASH UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Economics |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10205480 |
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