Dec 8, 2024
Rookie: Richter, how do I get revenge on my enemies?
Richter: The best revenge is letting go and living your life to the fullest.
Rookie: ...
Rookie: Skif-
Skif: Brick.
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Rookie: Richter, how do I get revenge on my enemies?
Richter: The best revenge is letting go and living your life to the fullest.
Rookie: ...
Rookie: Skif-
Skif: Brick.
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Links around Social Web Privacy
Wiki User Stories around Social Web If you add more user stories to add, you could send an email to [email protected]
List of Discussions Topics for the Social Web XG
ZoneTag project used geo-tagged photos and social networks to do face detection
Lifelogging: Privacy and Empowerment with Memories for Life (pdf) by Kieron O’Hara, Mischa M. Tuffield and Nigel Shadbolt
The growth of information acquisition, storage and retrieval capacity has led to the development of the practice of lifelogging, the undiscriminating collection of information concerning one’s life and behaviour. There are potential problems in this practice, but equally it could be empowering for the individual, and provide a new locus for the construction of an online identity. In this paper we look at the technological possibilities and constraints for lifelogging tools, and set out some of the most important privacy, identity and empowerment-related issues. We argue that some of the privacy concerns are overblown, and that much research and commentary on lifelogging has made the unrealistic assumption that the information gathered is for private use, whereas, in a more socially-networked online world, much of it will have public functions and will be voluntarily released into the public domain.
Data Republishing on the Social Web (pdf) by Claudia Wagner and Enrico Motta
Data Republishing is a recent Social Web phenomenon which can be observed in different areas of the Social Web. However, current Data Republishing tools don’t work in the emerging context of the Se- mantic Web. In particular, these tools neither generate any semantic metadata which provide information about the republished content (e.g., provenance information) nor are they able to make use of existing seman- tic metadata annotating the original content being republished. In this work we introduce the concept of Semantic Data Republishing and de- scribe how to implement it.
Collective Privacy Management in Social Networks (pdf) by Anna C. Squicciarini, Mohamed Shehab and Federica Paci
Social Networking is one of the major technological phe- nomena of the Web 2.0, with hundreds of millions of people participating. Social networks enable a form of self expres- sion for users, and help them to socialize and share content with other users. In spite of the fact that content sharing represents one of the prominent features of existing Social Network sites, Social Networks yet do not support any mech- anism for collaborative management of privacy settings for shared content. In this paper, we model the problem of collaborative enforcement of privacy policies on shared data by using game theory. In particular, we propose a solu- tion that offers automated ways to share images based on an extended notion of content ownership. Building upon the Clarke-Tax mechanism, we describe a simple mechanism that promotes truthfulness, and that rewards users who pro- mote co-ownership. We integrate our design with inference techniques that free the users from the burden of manually selecting privacy preferences for each picture. To the best of our knowledge this is the first time such a protection mechanism for Social Networking has been pro- posed. In the paper, we also show a proof-of-concept appli- cation, which we implemented in the context of Facebook, one of today’s most popular social networks. We show that supporting these type of solutions is not also feasible, but can be implemented through a minimal increase in overhead to end-users.