Abstract
The availability of real-time and reliable social signals is a necessity for implementing closed-loop and feedback based dynamic social management. However, the concepts and methods for social signals are far behind those for physical signal processing and analysis, and need to be developed in a systematic approach. As social and new media and social networking reach to all corners of societies rapidly, the problem of social signal processing and analysis becomes significant and the demand for effective solutions is great and urgent. This paper investigates issues related to the modeling and management of social systems, characterization of social signals and channels, social sensors and construction of social sensing networks, artificial societies, computational experiments, and parallel execution (the ACP approach) for reasoning and synthesis in computational social systems, computational dialectics, and computational analytics. Our objective is to establish a framework and methodology for acquisition, processing, analysis, analytics, and application of social signals.
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