Conference Proceedings


Barry Smyth
Alan F. Smeaton
Graham Healy
Steven Bourke


Computer Science

recommender systems experimentation computer networks electroencephalography human factors human computer interaction online social networks recommender systems information filtering

Introducing social networks and brain computer interaction (2012)

Abstract It is well known that the brain generates electrical patterns of activity in response to visual stimuli such as faces or any- thing that captures attention in a significant way. Signals of this type can be detected using an EEG (Electroencephalograph) system where we attach electrodes to the scalp and we amplify the detected signals and use a computer to capture them in real time. In this paper we examine the role that automatic sensing of brain activity may have on how users interact with interactive applications like Facebook. This offers a new opportunity for implicit feedback into such systems and in our work we focus on social networking applications. We demonstrate some of these implicit responses with experimental data captured while a user searched Facebook for photos of friends while being connected to an EEG. Finally, we discuss the implications that this kind of automatic implicit feedback may have on future design of such systems.
Collections Ireland -> University College Dublin -> Institutes and Centres
Ireland -> University College Dublin -> CLARITY Research Collection
Ireland -> University College Dublin -> College of Science
Ireland -> University College Dublin -> CLARITY: Centre for Sensor Web Technologies
Ireland -> University College Dublin -> School of Computer Science
Ireland -> University College Dublin -> Computer Science Research Collection

Full list of authors on original publication

Barry Smyth, Alan F. Smeaton, Graham Healy, Steven Bourke

Experts in our system

Barry Smyth
University College Dublin
Total Publications: 171
Alan F. Smeaton
Dublin City University
Total Publications: 492
Graham Healy
Dublin City University
Total Publications: 34