Learning to share: engineering adaptive decision-support for online social networks
Yasmin, Rafiq, Dickens, Luke, Russo, Alessandra, Bandara, Arosha, Yang, Mu, Stuart, Avelie, Levine, Mark, Calikli, Gul, Price, Blaine and Nuseibeh, Bashar (2017) Learning to share: engineering adaptive decision-support for online social networks. In: 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE). IEEE, pp. 280-285. ISBN 978-1538639764 (doi:10.1109/ASE.2017.8115641)
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Abstract
Some online social networks (OSNs) allow users to define friendship-groups as reusable shortcuts for sharing information with multiple contacts. Posting exclusively to a friendship-group gives some privacy control, while supporting communication with (and within) this group. However, recipients of such posts may want to reuse content for their own social advantage, and can bypass existing controls by copy-pasting into a new post; this cross-posting poses privacy risks. This paper presents a learning to share approach that enables the incorporation of more nuanced privacy controls into OSNs. Specifically, we propose a reusable, adaptive software architecture that uses rigorous runtime analysis to help OSN users to make informed decisions about suitable audiences for their posts. This is achieved by supporting dynamic formation of recipient-groups that benefit social interactions while reducing privacy risks. We exemplify the use of our approach in the context of Facebook.
Item Type: | Conference Proceedings |
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Title of Proceedings: | 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE) |
Additional Information: | Conference held from 30 Oct-3 Nov. 2017, Urbana, IL, USA. |
Uncontrolled Keywords: | privacy, Facebook, monitoring, sensitivity, computational modeling, adaptation models |
Subjects: | H Social Sciences > HM Sociology |
Faculty / School / Research Centre / Research Group: | Faculty of Business Faculty of Business > Department of Systems Management & Strategy |
Last Modified: | 30 Apr 2020 16:11 |
URI: | http://gala.gre.ac.uk/id/eprint/19823 |
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