Systems, Man & Cybernetics - April 2015 - 11

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beliefs about the social setting (e.g., making them aware of
a conflict or disagreement).
SSP is the computing domain aimed at the modeling,
analysis, and synthesis of social signals in human-human
and human-machine interactions [4]-[6]. Modeling refers to
the study of principles and laws that govern the use of social
signals. Analysis is the development of automatic approaches capable of detecting and interpreting social signals (e.g.,
understanding whether a smile communicates sympathy
or sarcasm). Synthesis is the generation of artificial social
signals that produce the same effects as those displayed by
humans (e.g., synthesizing voices that sound extraverted
or competent). Overall, the key idea of SSP-inspired by
several decades of research in social psychology-is that
social signals are the physical, machine-detectable traces
of psychological and social phenomena (e.g., conflict, empathy, interest, and emotions). These cannot be observed and
sensed directly but only inferred from the behavior of others.
SSP is still a young domain; the term SSP was coined
fewer than ten years ago [4], and, so far, it has focused
mainly on one particular type of social signals, i.e., the nonverbal behavioral cues (such as facial expressions, gestures,
and vocalizations) that people exchange in face-to-face,
colocated interactions. This is not surprising given that
such a setting is the primary site of human sociality [7], and
the very ability to exchange social signals is the result of an
evolutionary process during which face-to-face interactions
were the only ones possible [8]. Furthermore, nonverbal
cues tend to be displayed outside conscious awareness and,
therefore, tend to be honest, i.e., to convey reliable information independently of the intention to do so [9].
SSP extends the scope of other computing domains
revolving around human behavior, such as affective computing (focusing mainly on emotions), action recognition
(focusing on what people do rather than on social and
psychological motivations underlying actions), and automatic speech recognition and natural language processing
(focusing on verbal rather than nonverbal aspects of communication). In other words, SSP fills a gap left open by

other machine intelligence domains dealing with people
involved in colocated social interactions.
One of the most notable phenomena of the last
decade is that mobile technologies and social networking platforms have significantly multiplied the chances
for social interaction. Nowadays, people can interact
with virtually anybody at nearly every moment [10]. As
a result, social interactions take place increasingly
more frequently through technology and not necessarily face to face. According to the latest statistics [1],
Ap ri l 2015

IEEE Systems, Man, & Cybernetics Magazine

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Table of Contents for the Digital Edition of Systems, Man & Cybernetics - April 2015

Systems, Man & Cybernetics - April 2015 - Cover1
Systems, Man & Cybernetics - April 2015 - Cover2
Systems, Man & Cybernetics - April 2015 - 1
Systems, Man & Cybernetics - April 2015 - 2
Systems, Man & Cybernetics - April 2015 - 3
Systems, Man & Cybernetics - April 2015 - 4
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Systems, Man & Cybernetics - April 2015 - 11
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Systems, Man & Cybernetics - April 2015 - 47
Systems, Man & Cybernetics - April 2015 - 48
Systems, Man & Cybernetics - April 2015 - Cover3
Systems, Man & Cybernetics - April 2015 - Cover4
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