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Social Audio: Conceptualizing Voice-Based Online Social Networks and their Privacy Implications
Journal
Annual Meeting of the Academy of Management (AOM)
Type
conference paper
Date Issued
2023
Author(s)
Research Team
IWI6
Abstract
This paper explores the nature and implications of social audio: online social networks (OSNs) that enable users to interact via voice. The paper contributes to basic science by offering a precise conceptualization of voice-based OSNs and their design features. We posit that the defining characteristics of traditional OSNs also hold for social audio, yet that novel features (i.e., creating rooms) and modifications of traditional features (i.e., like) through voice idiosyncrasies can be found. This work also shows how social audio introduces novel privacy implications, particularly driven by the richness and risks of voice as an interaction modality. Using three illustrative cases, we demonstrate applications of social audio and how privacy implications remain largely unaddressed. Specifically, we find that the networks considered show very few specific features addressing the risks of voice-based interaction and that current privacy policies do not reflect these risks nor offer mitigation measures. We bridge our findings and extensions for future research by discussing potential approaches in terms of network architecture features for social audio providers to pursue in order to ensure user privacy.
Language
English
Keywords
voice
online social networks
user privacy
privacy concerns
HSG Classification
contribution to scientific community
Publisher place
Boston, Massachusetts, USA
Event Title
Annual Meeting of the Academy of Management (AOM)
Event Location
Boston, Massachusetts, USA
Event Date
04-08 Aug 2023
Subject(s)
Division(s)
Eprints ID
270062