Toward Context-Aware Privacy Enhancing Technologies for Online Self-Disclosure

Voluntary sharing of personal information is at the heart of user engagement on social media and central to platforms' business models. From the users' perspective, so-called self-disclosure is closely connected with both privacy risks and social rewards. Prior work has studied contextual influences on self-disclosure, from platform affordances and interface design to user demographics and perceived social capital. Our work takes a mixed-methods approach to understand the contextual information which might be integrated in the development of privacy-enhancing technologies. Through observational study of several Reddit communities, we explore the ways in which topic of discussion, group norms, peer effects, and audience size are correlated with personal information sharing. We then build and test a prototype privacy-enhancing tool that exposes these contextual factors. Our work culminates in a browser extension that automatically detects instances of self-disclosure in Reddit posts at the time of posting and provides additional context to users before they post to support enhanced privacy decision-making. We share this prototype with social media users, solicit their feedback, and outline a path forward for privacy-enhancing technologies in this space.

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Publication Details

Journal
Proceedings of the AAAI Conference on Human Computation and Crowdsourcing
Published
2024-10-14
DOI
https://doi.org/10.1609/hcomp.v12i1.31599
Primary Topic
Privacy-Preserving Technologies in Data
Type
article
Field-Weighted Citation Impact
0.00
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article

Toward Context-Aware Privacy Enhancing Technologies for Online Self-Disclosure

Anna Squicciarini, Sarah Michele Rajtmajer, Tingting Du, Jiyoon Kim
Proceedings of the AAAI Conference on Human Computation and Crowdsourcing
Privacy-Preserving Technologies in Data
article

Toward Context-Aware Privacy Enhancing Technologies for Online Self-Disclosure

Anna Squicciarini, Sarah Michele Rajtmajer, Tingting Du, Jiyoon Kim
article en

Abstract

Voluntary sharing of personal information is at the heart of user engagement on social media and central to platforms' business models. From the users' perspective, so-called self-disclosure is closely connected with both privacy risks and social rewards. Prior work has studied contextual influences on self-disclosure, from platform affordances and interface design to user demographics and perceived social capital. Our work takes a mixed-methods approach to understand the contextual information which might be integrated in the development of privacy-enhancing technologies. Through observational study of several Reddit communities, we explore the ways in which topic of discussion, group norms, peer effects, and audience size are correlated with personal information sharing. We then build and test a prototype privacy-enhancing tool that exposes these contextual factors. Our work culminates in a browser extension that automatically detects instances of self-disclosure in Reddit posts at the time of posting and provides additional context to users before they post to support enhanced privacy decision-making. We share this prototype with social media users, solicit their feedback, and outline a path forward for privacy-enhancing technologies in this space.

Proceedings of the AAAI Conference on Human Computation and CrowdsourcingVol. 12
Pennsylvania State University (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 84%
Privacy-Preserving Technologies in Data
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Toward Context-Aware Privacy Enhancing Technologies for Online Self-Disclosure — Anna Squicciarini, Sarah Michele Rajtmajer, et al. · Proceedings of the AAAI Conference on Human Computation and Crowdsourcing (2024) | TGRS Research Map | TGRS