OmniWedges: Improved Radar-Based Audience Selection for Social Networks

Frederic Raber, Antonio Krüger

In: David Lamas , Fernando Loizides , Lennart Nacke , Helen Petrie , Marco Winckler , Panayiotis Zaphiris (Hrsg.). Human-Computer Interaction -- INTERACT 2019. IFIP Conference on Human-Computer Interaction (INTERACT-2019) September 2-6 Paphos Greece Seiten 654-658 ISBN 978-3-030-29390-1 Springer International Publishing 2019.


Selecting the right audience for Facebook posts is a task that users often skip, resulting in unwanted post disclosure or avoidance of sharing sensitive posts. We present OmniWedges, a user interface designed to allow users of online social networks to make meaningful decisions on who to share their posts with. Our study results also show that with all Facebook friends, the error rate can be significantly reduced compared to the Facebook interface. In an interview, we were also able to spot a change in posting behavior and frequency with our interface.


submission.pdf (pdf, 1 MB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence