%0 Conference Paper %1 ls_leimeister %A Schmitt, Anuschka %A Rentsch, Stefanie %A Janson, Andreas %B Annual Meeting of the Academy of Management (AOM) %C Boston, Massachusetts, USA %D 2023 %K itegpub online_social_networks privacy_concerns pub_aja u3bpub user_privacy voice %T Social Audio: Conceptualizing Voice-Based Online Social Networks and their Privacy Implications %X 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.

@inproceedings{ls_leimeister, 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.}, added-at = {2023-04-08T10:57:03.000+0200}, address = {Boston, Massachusetts, USA}, author = {Schmitt, Anuschka and Rentsch, Stefanie and Janson, Andreas}, biburl = {https://www.bibsonomy.org/bibtex/2f45721c0b8eb0f80fb08d4c56ea8c649/ls_leimeister}, booktitle = {Annual Meeting of the Academy of Management (AOM)}, eventdate = {04-08 Aug 2023}, eventtitle = {Annual Meeting of the Academy of Management (AOM)}, interhash = {b67eec9b2f75018b5f4de7666ff3a67e}, intrahash = {f45721c0b8eb0f80fb08d4c56ea8c649}, keywords = {itegpub online_social_networks privacy_concerns pub_aja u3bpub user_privacy voice}, language = {English}, timestamp = {2023-04-08T10:57:03.000+0200}, title = {Social Audio: Conceptualizing Voice-Based Online Social Networks and their Privacy Implications}, venue = {Boston, Massachusetts, USA}, year = 2023 }