Title :
Circles, posts and privacy in egocentric social networks: An exploratory visualization approach
Author :
Bo Gao ; Berendt, Bettina
Author_Institution :
Dept. of Comput. Sci., KU Leuven, Leuven, Belgium
Abstract :
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.
Keywords :
Internet; data privacy; data visualisation; social networking (online); OSN; circles; community discovery methods; egocentric social networks; exploratory visualization approach; fine grained control; online social networks; posts; privacy; private information; visibility decisions; visualization design; Algorithm design and analysis; Communities; Facebook; Manuals; Privacy; Visualization; Circles; Design; Online Social Networks; Privacy; Visualization;
Conference_Titel :
Advances in Social Networks Analysis and Mining (ASONAM), 2013 IEEE/ACM International Conference on
Conference_Location :
Niagara Falls, ON