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Publications

This page contains the deliverables and scientific output of

the Serendipity Engine project. Contact us for more information about

the publications and reports.

Scientific publications

How Should We Measure Filter Bubbles? A Regression Model and Evidence for Online News

Michiels, L., Vannieuwenhuyze, J., Leysen, J., Verachtert, R., Smets, A., & Goethals, B. (2023). How Should We Measure Filter Bubbles? A Regression Model and Evidence for Online News. In Proceedings of the 17th ACM Conference on Recommender Systemshttps://doi.org/10.1145/3604915.3608805

Towards a Pragmatic Approach for Studying Normative Recommender Systems: Exploring Power Dynamics in Digital Platform Markets

Binst, B., Vandenbroucke, H.,  Li, D., Puskas, I., Van der Elst, P. & Smets, A. (2023). Towards a Pragmatic Approach for Studying Normative Recommender Systems: Exploring Power Dynamics in Digital Platform Markets. The First Workshop on Normative Design and Evaluation of Recommender Systems.

A Framework and Toolkit for Testing the Correctness of Recommendation Algorithms

Michiels, L., Verachtert, R., Ferraro, A., Falk, K., & Goethals, B. (2023). A Framework and Toolkit for Testing the Correctness of Recommendation Algorithms. ACM Transactions on Recommender Systemshttps://dl.acm.org/doi/pdf/10.1145/3591109

Designing for Serendipity, a Means or an End?

Smets, A. (2023). Designing for serendipity: a means or an end?. Journal of Documentation, 79(3), 589-607. https://doi.org/10.1108/JD-12-2021-0234

Serendipity in Recommender Systems Beyond the Algorithm: A Feature Repository and Experimental Design

Smets, A., Michiels, L., Bogers, T., & Björneborn, L. (2022). Serendipity in Recommender Systems Beyond the Algorithm: A Feature Repository and Experimental Design. In 16th ACM Conference on Recommender Systems. CEUR Workshop Proceedings (pp. 44-66). https://ceur-ws.org/Vol-3222/paper4.pdf

 What Are Filter Bubbles Really? A Review of the Conceptual and Empirical Work

Michiels, L., Leysen, J., Smets, A., & Goethals, B. (2022). What Are Filter Bubbles Really? A Review of the Conceptual and Empirical Work. In Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization (pp. 274-279). https://doi.org/10.1145/3511047.3538028

Michiels, L., Verachtert, R., & Goethals, B. (2022). RecPack: An (other) Experimentation Toolkit for Top-N Recommendation using Implicit Feedback Data. In Proceedings of the 16th ACM Conference on Recommender Systems (pp. 648-651). https://doi.org/10.1145/3523227.3551472

Methodological Analysis of Personalization in Urban Recommender Systems by Distance Measures. 

Vannieuwenhuyze, J., Smets, A., Gebert, M., & Ballon, P. (2022). Methodological Analysis of Personalization in Urban Recommender Systems by Distance Measures. Telematics and Informatics, 71.  https://doi.org/10.1016/j.tele.2022.101818  

Mediated by Code: Unpacking Algorithmic Curation of Urban Experiences

Smets, A., Ballon, P., & Walravens, N. (2021). Mediated by Code: Unpacking Algorithmic Curation of Urban Experiences. Media and Communication, 9(4), 250-259. https://doi.org/10.17645/mac.v9i4.4086 

 Using Regions of Interest for Personalized Route Planning

Delva, H., Smets, A., Colpaert, P., Ballon, P., & Verborgh, R. (2020). Using Regions of Interest for Personalized Route Planning. In Proceedings of the 2nd International Workshop on Semantics for Transport (pp. 47-52). Springer. 
https://link.springer.com/chapter/10.1007/978-3-030-65665-2_5

Does the bubble go beyond? An exploration of the urban filter bubble.

Smets, A., Montero, E., & Ballon, P. (2019). Does the bubble go beyond? An exploration of the urban filter bubble. In The 1st Workshop on the Impact of Recommender Systems with ACM RecSys 2019 (Vol. 2462).  CEUR Workshop Proceedings. http://ceur-ws.org/Vol-2462/paper3.pdf

Presentations at academic conferences

Let go of the one-size-fits-all definition of serendipity

Smets, A. (2023). Let go of the one-size-fits-all definition of serendipity. 3rd International Conference of Possibility Studies. July 20, 2023, Dublin. -- Abstract

Best practices for offline evaluation

Lien, M. (2023). Best practices for offline evaluation. ACM RecSys Summer School. June 12, 2023, Copenhagen.

Reports

List of Design Interventions

Advisory Committee 25 April 2023

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