Aridor, Guy;
Goncalves, Duarte;
Sikdar, Shan;
(2020)
Deconstructing the Filter Bubble: User Decision-Making and Recommender Systems.
In:
Proceedings of the 14th ACM Conference on Recommender Systems.
(pp. pp. 82-91).
ACM: New York, NY, USA.
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Abstract
We study a model of user decision-making in the context of recommender systems via numerical simulation. Our model provides an explanation for the findings of Nguyen, et. al (2014), where, in environments where recommender systems are typically deployed, users consume increasingly similar items over time even without recommendation. We find that recommendation alleviates these natural filter-bubble effects, but that it also leads to an increase in homogeneity across users, resulting in a trade-off between homogenizing across-user consumption and diversifying within-user consumption. Finally, we discuss how our model highlights the importance of collecting data on user beliefs and their evolution over time both to design better recommendations and to further understand their impact.
| Type: | Proceedings paper |
|---|---|
| Title: | Deconstructing the Filter Bubble: User Decision-Making and Recommender Systems |
| Event: | RecSys '20: Fourteenth ACM Conference on Recommender Systems |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3383313.3412246 |
| Publisher version: | https://doi.org/10.1145/3383313.3412246 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Filter Bubbles, Recommender Systems, Similarity-based Generalization |
| 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-pp.ucl.ac.uk/id/eprint/10168775 |
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