%0 Conference Proceedings
%T OmniWedges: Improved Radar-Based Audience Selection for Social Networks
%+ Deutsches Forschungszentrum für Künstliche Intelligenz GmbH = German Research Center for Artificial Intelligence (DFKI)
%A Raber, Frederic
%A Krüger, Antonio
%Z Part 10: Interactive Posters
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 17th IFIP Conference on Human-Computer Interaction (INTERACT)
%C Paphos, Cyprus
%Y David Lamas
%Y Fernando Loizides
%Y Lennart Nacke
%Y Helen Petrie
%Y Marco Winckler
%Y Panayiotis Zaphiris
%I Springer International Publishing
%3 Human-Computer Interaction – INTERACT 2019
%V LNCS-11749
%N Part IV
%P 654-658
%8 2019-09-02
%D 2019
%R 10.1007/978-3-030-29390-1_56
%Z Computer Science [cs]Conference papers
%X 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.
%G English
%Z TC 13
%2 https://inria.hal.science/hal-02878626/document
%2 https://inria.hal.science/hal-02878626/file/488595_1_En_56_Chapter.pdf
%L hal-02878626
%U https://inria.hal.science/hal-02878626
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC13
%~ IFIP-INTERACT
%~ IFIP-LNCS-11749