Rafiq, Y;
Dickens, L;
Russo, A;
Bandara, AK;
Yang, M;
Stuart, A;
Levine, M;
... Nuseibeh, B; + view all
(2017)
Learning to Share: Engineering Adaptive Decision-Support for Online Social Networks.
In: Rosu, G and DiPenta, M and Nguyen, TN, (eds.)
(Proceedings) 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE).
(pp. pp. 280-285).
IEEE
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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.
| Type: | Proceedings paper |
|---|---|
| Title: | Learning to Share: Engineering Adaptive Decision-Support for Online Social Networks |
| Event: | 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE) |
| Location: | Univ Illinois Urbana Champaign, Urbana Champaign, IL |
| Dates: | 29 October 2017 - 03 November 2017 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/ASE.2017.8115641 |
| Publisher version: | https://doi.org/10.1109/ASE.2017.8115641 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Science & Technology, Technology, Computer Science, Software Engineering, Engineering, Electrical & Electronic, Computer Science, Engineering, PRIVACY CALCULUS, MODEL |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science UCL > Provost and Vice Provost Offices > UCL SLASH UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of Arts and Humanities UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of Arts and Humanities > Dept of Information Studies |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10044301 |
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