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Self-imposed filter bubble model for argumentative dialogues

  • During their information seeking people tend to filter out all the parts of the available information that do not fit their existing beliefs or opinions. In this paper we present a model for this “Self-imposed Filter Bubble” (SFB) consisting of four dimensions. Thereby, we aim to 1) estimate the probability of the user being caught in an SFB and consequently, 2) identify suitable clues to reduce this probability in the further course of a dialogue. Using an exemplary implementation in an argumentative dialogue system, we demonstrate the validity and applicability of this model in an online user study with 102 participants. These findings serve as a basis for developing a system strategy to break the user’s SFB and contribute to a sustainable and profound reflection on a topic from all viewpoints.

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Metadaten
Author:Annalena AicherORCiDGND, Daniel Kornmüller, Wolfgang Minker, Stefan Ultes
URN:urn:nbn:de:bvb:384-opus4-1229453
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/122945
ISBN:979-8-4007-0014-9OPAC
Parent Title (English):CUI '23: proceedings of the 5th International Conference on Conversational User Interfaces, Eindhoven, Netherlands, July 19-21, 2023
Publisher:Association for Computing Machinery (ACM)
Place of publication:New York, NY
Editor:Minha Lee, Cosmin Munteanu, Martin Porcheron, Johanne Trippas, Sarah Theres Völkel
Type:Conference Proceeding
Language:English
Year of first Publication:2023
Publishing Institution:Universität Augsburg
Release Date:2025/06/25
First Page:23
DOI:https://doi.org/10.1145/3571884.3597131
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Menschzentrierte Künstliche Intelligenz
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)

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