Managing Temporal Dynamics of Filter Bubbles

Date
2022-01-04
Authors
Hirschmeier, Stefan
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Abstract
Filter bubbles have attracted much attention in recent years in terms of their impact on society. Whereas it is commonly agreed that filter bubbles should be managed, the question is still how. We draw a picture of filter bubbles as dynamic, slowly changing constructs that underlie temporal dynamics and that are constantly influenced by both machine and human. Anchored in a research setting with a major public broadcaster, we follow a design science approach on how to design the temporal dynamics in filter bubbles and how to design users' influence over time. We qualitatively evaluate our approach with a smartphone app for personalized radio and found that the adjustability of filter bubbles leads to a better co-creation of information flows between information broadcaster and listener.
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Accountability, Evaluation, and Obscurity of AI Algorithms, audio streaming, filter bubble, temporal dynamics
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