Privacy Policy Negotiation in Social Media
- Submitting institution
-
King's College London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 87323490
- Type
- D - Journal article
- DOI
-
10.1145/2821512
- Title of journal
- ACM TRANSACTIONS ON AUTONOMOUS AND ADAPTIVE SYSTEMS
- Article number
- 4
- First page
- -
- Volume
- 11
- Issue
- 1
- ISSN
- 1556-4665
- Open access status
- Out of scope for open access requirements
- Month of publication
- February
- Year of publication
- 2016
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- Yes
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
1
- Research group(s)
-
-
- Citation count
- 23
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper started the important area of automatically supporting privacy management for co-owned items. Previous approaches relied completely on extensive user intervention, which made the process cumbersome. This paper proposed a rigorous game-theoretic perspective, together with a complexity analysis and a set of near-optimal heuristics that were empirically demonstrated to be applicable in real-world social media. This paper was included in the ACM Annual Best of Computing (2016), and the presented research results supported the EPSRC EP/M027805/1 application (ranked 1st in panel).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -