Mathematical foundations of social sensing
An introductory tutorial
Abstract
After reviewing the emerging trends and applications in social sensing, this chapter reviews mathematical foundations and basic technologies that we will use throughout this book. These foundations include basics of information networks, Bayesian analysis, maximum likelihood estimation, expectation maximization, as well as bounds and confidence intervals in estimation theory. Some illustrative examples are used to demonstrate the basic concepts and principles related with covered foundations. The chapter concludes with an analytical framework that allows us to put all these foundations together.
Keywords
Mathematical foundation
Information networks
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