Does the Bubble Go Beyond? An Exploration of the Urban Filter Bubble. - Annelien Smets; Eladio Montero; Pieter Ballon (ImpactRS@RecSys, 2019)

Interactive Route Personalization Using Regions of Interest. - Harm Delva; Annelien Smets; Pieter Colpaert; Pieter Ballon; Ruben Verborgh (ICWE Workshops, 2020)

Designing Recommender Systems for the Common Good. - Annelien Smets; Nils Walravens; Pieter Ballon (UMAP (Adjunct Publication), 2020)

Blind Spots in AI: the Role of Serendipity and Equity in Algorithm-Based Decision-Making. - Cora van Leeuwen; Annelien Smets; An Jacobs; Pieter Ballon (SIGKDD Explor., 2021)

Serendipity in Recommender Systems Beyond the Algorithm: a Feature Repository and Experimental Design. - Annelien Smets; Lien Michiels; Toine Bogers; Lennart Björneborn (IntRS@RecSys, 2022)

What Are Filter Bubbles Really? A Review of the Conceptual and Empirical Work. - Lien Michiels; Jens Leysen; Annelien Smets; Bart Goethals (UMAP (Adjunct Publication), 2022)

Serendipity in the city: User evaluations of urban recommender systems. - Annelien Smets; Jorre T. A. Vannieuwenhuyze; Pieter Ballon (J. Assoc. Inf. Sci. Technol., 2022)

Methodological analysis of personalization in urban recommender systems by distance measures. - Jorre T. A. Vannieuwenhuyze; Annelien Smets; Martin Gebert; Pieter Ballon (Telematics Informatics, 2022)

Towards a Pragmatic Approach for studying Normative Recommender Systems: exploring Power Dynamics in Digital Platform Markets. - Brett Binst; Hanne Vandenbroucke; Donqxiao Li; Isabelle Puskas; Pieter Van der Elst; Annelien Smets (NORMalize@RecSys, 2023)

How Should We Measure Filter Bubbles? A Regression Model and Evidence for Online News. - Lien Michiels; Jorre T. A. Vannieuwenhuyze; Jens Leysen; Robin Verachtert; Annelien Smets; Bart Goethals (RecSys, 2023)

Designing for serendipity: a means or an end? - Annelien Smets (J. Documentation, 2023)

GenUI(ne) CRS: UI Elements and Retrieval-Augmented Generation in Conversational Recommender Systems with LLMs. - Ulysse Maes; Lien Michiels; Annelien Smets (RecSys, 2024)

It's (not) all about that CTR: A Multi-Stakeholder Perspective on News Recommender Metrics. - Hanne Vandenbroucke; Annelien Smets (RecSys, 2024)

Mitigating Misleadingness in LLM-Generated Natural Language Explanations for Recommender Systems: Ensuring Broad Truthfulness Through Factuality and Faithfulness. - Ulysse Maes; Lien Michiels; Annelien Smets (IUI Workshops, 2025)

What Is Serendipity? An Interview Study to Conceptualize Experienced Serendipity in Recommender Systems. - Brett Binst; Lien Michiels; Annelien Smets (UMAP, 2025)

A Bourdieusian theory on communicating an opinion about AI governance. - Brett Binst; Tuba Bircan; Annelien Smets (AI Soc., 2025)

Intended, afforded, and experienced serendipity: overcoming the paradox of artificial serendipity. - Annelien Smets (Ethics Inf. Technol., 2025)