Social sensing: obesity, unhealthy eating and exercise in face-to-face networks
WH '10 Wireless Health 2010
Pervasive sensing to model political opinions in face-to-face networks
Pervasive'11 Proceedings of the 9th international conference on Pervasive computing
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By building machines that understand social signaling and social context, we can dramatically improve collective decision making and help keep remote users 'in the loop.' I will describe three systems that have a substantial understanding of social context, and use this understanding to improve human group performance. The first system is able to interpret social displays of interest and attraction, and uses this information to improve conferences and meetings. The second is able to infer friendship, acquaitance, and workgroup relationships, and uses this to help people build social capital. The third is able to examine human interactions and categorize participants attitudes (attentive, agreeable, determined, interested, etc), and uses this information to proactively promote group cohesion and to match participants on the basis of their compatiblity.