中国科学院自动化研究所机构知识库

实时、可靠的社会信号, 是实施有效的社会管理, 特别是反馈闭环式的社会管理创新的基础.

然而, 相对于物理信号, 社会信号的处理与分析有待系统化的研究与发展. 随着社会新媒体和社会网络的蓬勃兴起和普及, 这一问题变得更加迫切和急需. 本文就社会信号与社会系统建模与管理, 社会信号的刻画, 社会传感网的构建, 计算辩证推理和综合的人工社会、计算实验、平行执行(ACP) 方法等展开讨论, 希望在此基础上进一步开展研究与应用, 最终建立面向社会信号之获取、分析、解析和应用的一般框架与方法体系.

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.