Managing Temporal Dynamics of Filter Bubbles

Simple item page
dc.contributor.authorHirschmeier, Stefan
dc.date.accessioned2021-12-24T17:26:05Z
dc.date.available2021-12-24T17:26:05Z
dc.date.issued2022-01-04
dc.description.abstractFilter 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.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2022.133
dc.identifier.isbn978-0-9981331-5-7
dc.identifier.urihttp://hdl.handle.net/10125/79465
dc.language.isoeng
dc.relation.ispartofProceedings of the 55th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectAccountability, Evaluation, and Obscurity of AI Algorithms
dc.subjectaudio streaming
dc.subjectfilter bubble
dc.subjecttemporal dynamics
dc.titleManaging Temporal Dynamics of Filter Bubbles
dc.type.dcmitext

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
0107.pdf
Size:
1004.13 KB
Format:
Adobe Portable Document Format
Download

Collections

Accountability, Evaluation, and Obscurity of AI Algorithms