The Effectiveness of Adaptation Methods in Improving User Engagement and Privacy Protection on Social Network Sites

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 diffe...

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Autores principales: Namara Moses, Sloan Henry, Knijnenburg Bart P.
Formato: article
Lenguaje:EN
Publicado: Sciendo 2022
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Acceso en línea:https://doaj.org/article/b25462dc860e445086741d80e899de4a
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spelling oai:doaj.org-article:b25462dc860e445086741d80e899de4a2021-12-05T14:11:10ZThe Effectiveness of Adaptation Methods in Improving User Engagement and Privacy Protection on Social Network Sites2299-098410.2478/popets-2022-0031https://doaj.org/article/b25462dc860e445086741d80e899de4a2022-01-01T00:00:00Zhttps://doi.org/10.2478/popets-2022-0031https://doaj.org/toc/2299-0984Research 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 between-subjects 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.Namara MosesSloan HenryKnijnenburg Bart P.Sciendoarticleprivacysocial mediafacebookuser-tailored privacyprivacy on social mediaprivacy decision-makingEthicsBJ1-1725Electronic computers. Computer scienceQA75.5-76.95ENProceedings on Privacy Enhancing Technologies, Vol 2022, Iss 1, Pp 629-648 (2022)
institution DOAJ
collection DOAJ
language EN
topic privacy
social media
facebook
user-tailored privacy
privacy on social media
privacy decision-making
Ethics
BJ1-1725
Electronic computers. Computer science
QA75.5-76.95
spellingShingle privacy
social media
facebook
user-tailored privacy
privacy on social media
privacy decision-making
Ethics
BJ1-1725
Electronic computers. Computer science
QA75.5-76.95
Namara Moses
Sloan Henry
Knijnenburg Bart P.
The Effectiveness of Adaptation Methods in Improving User Engagement and Privacy Protection on Social Network Sites
description 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 between-subjects 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.
format article
author Namara Moses
Sloan Henry
Knijnenburg Bart P.
author_facet Namara Moses
Sloan Henry
Knijnenburg Bart P.
author_sort Namara Moses
title The Effectiveness of Adaptation Methods in Improving User Engagement and Privacy Protection on Social Network Sites
title_short The Effectiveness of Adaptation Methods in Improving User Engagement and Privacy Protection on Social Network Sites
title_full The Effectiveness of Adaptation Methods in Improving User Engagement and Privacy Protection on Social Network Sites
title_fullStr The Effectiveness of Adaptation Methods in Improving User Engagement and Privacy Protection on Social Network Sites
title_full_unstemmed The Effectiveness of Adaptation Methods in Improving User Engagement and Privacy Protection on Social Network Sites
title_sort effectiveness of adaptation methods in improving user engagement and privacy protection on social network sites
publisher Sciendo
publishDate 2022
url https://doaj.org/article/b25462dc860e445086741d80e899de4a
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