The Effectiveness of Adaptation Methods in Improving User Engagement and Privacy Protection on Social Network Sites
Loading...
Date
2021
Journal Title
Journal ISSN
Volume Title
Publisher
Proceedings on Privacy Enhancing Technologies
Abstract
Research finds that the users of Social Networking
Sites (SNSs) often fail to comprehensively engage
with the plethora of available privacy features—
arguably due to their sheer number and the fact that
they are often hidden from sight. As different users are
likely interested in engaging with different subsets of
privacy features, an SNS could improve privacy management
practices by adapting its interface in a way
that proactively assists, guides, or prompts users to engage
with the subset of privacy features they are most
likely to benefit from. Whereas recent work presents algorithmic
implementations of such privacy adaptation
methods, this study investigates the optimal user interface
mechanism to present such adaptations. In particular,
we tested three proposed “adaptation methods” (automation,
suggestions, highlights) in an online betweensubjects
user experiment in which 406 participants used
a carefully controlled SNS prototype. We systematically
evaluate the effect of these adaptation methods
on participants’ engagement with the privacy features,
their tendency to set stricter settings (protection), and
their subjective evaluation of the assigned adaptation
method. We find that the automation of privacy features
afforded users the most privacy protection, while
giving privacy suggestions caused the highest level of engagement
with the features and the highest subjective
ratings (as long as awkward suggestions are avoided).
We discuss the practical implications of these findings
in the effectiveness of adaptations improving user awareness
of, and engagement with, privacy features on social
media.
Description
Keywords
Privacy, Social media, Privacy decision-making, Usertailored privacy
Citation
Namara, M., Sloan, H., & Knijnenburg, B. P. (2022). The Effectiveness of Adaptation Methods in Improving User Engagement and Privacy Protection on Social Network Sites. Proceedings on Privacy Enhancing Technologies, 2022(1), 629-648. DOI 10.2478/popets-2022-0031