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Interactive Sensing and Decision Making in Social Networks
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The proliferation of social media such as real time microblogging and online reputation systems facilitate real time sensing of social patterns and behavior. In the last decade, sensing and decision making in social networks has witnessed significant progress in the electrical engineering, computer science, economics, finance, and sociology research communities. Research in this area involves the interaction of dynamic random graphs, socio-economic analysis, and statistical inference algorithms. This monograph provides a survey, tutorial development, and discussion of four highly stylized examples: social learning for interactive sensing; tracking the degree distribution of social networks; sensing and information diffusion; and coordination of decision making via game-theoretic learning. Each of the four examples is motivated by practical examples, and comprises of a literature survey together with careful problem formulation and mathematical analysis. The examples and associated analysis are readily accessible to researchers in signal processing, control/systems theory, and applied mathematics.
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