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Learning to share: engineering adaptive decision-support for online social networks

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: Proceedings of the 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE 2017). IEEE, pp. 280-285. ISBN 978-1-5386-3976-4 (doi:https://doi.org/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
Title of Proceedings: Proceedings of the 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE 2017)
Additional Information: Conference held from 30 Oct-3 Nov. 2017, Urbana, IL, USA.
Uncontrolled Keywords: Privacy, Facebook, Monitoring, Sensitivity, Computational modeling, Adaptation models
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Department of Systems Management & Strategy
Related URLs:
Last Modified: 11 Jun 2019 10:32
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: GREAT a
Selected for GREAT 2019: GREAT 6
URI: http://gala.gre.ac.uk/id/eprint/19823

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