Annelien Smets
Annelien Smets
imec-SMIT, Vrije Universiteit Brussel
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Cited by
Cited by
What Are Filter Bubbles Really? A Review of the Conceptual and Empirical Work
L Michiels, J Leysen, A Smets, B Goethals
Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation …, 2022
We’re in This Together: A Multi-Stakeholder Approach for News Recommenders
A Smets, J Hendrickx, P Ballon
Digital Journalism, 1-19, 2022
Serendipity in the city: User evaluations of urban recommender systems
A Smets, J Vannieuwenhuyze, P Ballon
Journal of the Association for Information Science and Technology 73 (1), 19-30, 2021
News Recommender Systems and News Diversity, Two of a Kind? A Case Study from a Small Media Market
J Hendrickx, A Smets, P Ballon
Journalism and Media 2 (3), 515-528, 2021
Blind spots in AI: the role of serendipity and equity in algorithm-based decision-making
C van Leeuwen, A Smets, A Jacobs, P Ballon
ACM SIGKDD Explorations Newsletter 23 (1), 42-49, 2021
Human Sensemaking in the Smart City: A Research Approach Merging Big and Thick Data
A Smets, B Lievens
Ethnographic Praxis in Industry Conference Proceedings 2018 (1), 179-194, 2018
Serendipity in Recommender Systems Beyond the Algorithm: A Feature Repository and Experimental Design
A Smets, L Michiels, T Bogers, L Björneborn
16th ACM Conference on Recommender Systems, 44-66, 2022
Designing for serendipity: a means or an end?
A Smets
Journal of Documentation 79 (3), 589-607, 2023
Mediated by Code: Unpacking Algorithmic Curation of Urban Experiences
A Smets, P Ballon, N Walravens
Media and Communication 9 (3), 2021
Does the Bubble Go Beyond? An Exploration of the Urban Filter Bubble
A Smets, E Montero, P Ballon
15 Challenges and opportunities for recommender systems in media markets
H Ranaivoson, A Smets, P Ballon
De Gruyter Handbook of Media Economics, 215, 2024
How Should We Measure Filter Bubbles? A Regression Model and Evidence for Online News
L Michiels, J Vannieuwenhuyze, J Leysen, R Verachtert, A Smets, ...
Proceedings of the 17th ACM Conference on Recommender Systems, 640-651, 2023
Designing Recommender Systems for the Common Good
A Smets, N Walravens, P Ballon
Adjunct Publication of the 28th ACM Conference on User Modeling, Adaptation …, 2020
Context-Aware Experience Sampling Method to Understand Human Behavior in a Smart City: a Case Study
A Smets, B Lievens, R D’Hauwers
Measuring Behavior 2018, 2018
Nudging Sustainable Behaviour: The Use of Data-driven Nudges to Support a Circular Economy in Smart Cities
A Smets, B Lievens
Smart Cities in Smart Regions 2018, 151, 2018
Serendipity as a Shared Value in Urban Recommender Systems
A Smets
Phd thesis, Vrije Universiteit Brussel, 2022
Behaviour Monitoring in Context: a Methodology for Measuring the Impact of the Human Factor on Smart Cities Big Data and Technologies
F Spagnoli, S van der Graaf, A Smets
Measuring Behavior 2018, 2018
Using Regions of Interest for Personalized Route Planning
H Delva, A Smets, P Colpaert, P Ballon, R Verborgh
Proceedings of the 2nd International Workshop on Semantics for Transport, 47-52, 2020
Newsroom Realities: An Exploration of Changing Dynamics in News Organizations in Relation to Recommender Systems
H Vandenbroucke, A Smets
DBWRS: Dutch-Belgian workshop on Recommender Systems, 2023
Zomerblog: De gespannen relatie tussen digitalisering en serendipiteit
B Binst, A Smets
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