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Towards a Pragmatic Approach for studying Normative Recommender Systems: exploring Power Dynamics in Digital Platform Markets.

, , , , , and . NORMalize@RecSys, volume 3639 of CEUR Workshop Proceedings, CEUR-WS.org, (2023)

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Designing Recommender Systems for the Common Good., , and . UMAP (Adjunct Publication), page 276-278. ACM, (2020)What Are Filter Bubbles Really? A Review of the Conceptual and Empirical Work., , , and . UMAP (Adjunct Publication), page 274-279. ACM, (2022)Interactive Route Personalization Using Regions of Interest., , , , and . ICWE Workshops, volume 12451 of Lecture Notes in Computer Science, page 47-52. Springer, (2020)Serendipity in the city: User evaluations of urban recommender systems., , and . J. Assoc. Inf. Sci. Technol., 73 (1): 19-30 (2022)Methodological analysis of personalization in urban recommender systems by distance measures., , , and . Telematics Informatics, (2022)Towards a Pragmatic Approach for studying Normative Recommender Systems: exploring Power Dynamics in Digital Platform Markets., , , , , and . NORMalize@RecSys, volume 3639 of CEUR Workshop Proceedings, CEUR-WS.org, (2023)Designing for serendipity: a means or an end?. J. Documentation, 79 (3): 589-607 (2023)How Should We Measure Filter Bubbles? A Regression Model and Evidence for Online News., , , , , and . RecSys, page 640-651. ACM, (2023)Serendipity in Recommender Systems Beyond the Algorithm: a Feature Repository and Experimental Design., , , and . IntRS@RecSys, volume 3222 of CEUR Workshop Proceedings, page 46-66. CEUR-WS.org, (2022)Blind Spots in AI: the Role of Serendipity and Equity in Algorithm-Based Decision-Making., , , and . SIGKDD Explor., 23 (1): 42-49 (2021)