Circles, posts and privacy in egocentric social networks
Author(s) -
Bo Gao,
Bettina Berendt
Publication year - 2013
Publication title -
lirias (ku leuven)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/2492517.2492654
Subject(s) - computer science , visualization , visibility , human–computer interaction , world wide web , online community , social network (sociolinguistics) , exploratory research , information visualization , artificial intelligence , social media , physics , sociology , anthropology , optics
The users in Online Social Networks (OSN) may share private information with wrong friends. One approach to tackle this issue is by applying community discovery methods in egocentric networks to automatically generate friend circles for the user. There is however a discrepancy between the predicted circles and the circles that the user has in mind. A deep rooted reason is that it only makes sense when the circles are considered under certain usage. We designed and implemented an exploratory visualization tool that can help users determine the visibilities of their online posts. More specifically, we first examined the state-of-the-art community discovery methods for egocentric networks, then proposed a new visualization design with fine-grained control for the user to interact with the circles and make visibility decisions. Finally, we conducted an experimental user study evaluating the usefulness of this design.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom