Social signaling in decision making

Abstract

Nonverbal communication is an important and often underestimated instrument in social interactions. The paralinguistic elements of speech, which are described in common speech as "tone of voice", are one channel of the nonverbal communication. They, together with conversational dynamics, are a very powerful measurement for interactions, without looking at the content of the conversation. A subset of these features, the social signaling measurements, are very useful when analyzing and quantifying conversation. The goal of this thesis is to better understand the framework of social signaling. We applied the social signaling measurements to negotiations as well as to small group interactions. For negotiation we were able to predict up to 30% of the variance in individual outcome. The use of automated algorithms enables to build real-time feedback mechanisms that can then help users to improve and achieve their objectives.