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To date, most network research contains one or more of five major problems. First, it tends to be atheoretical, ignoring the various social theories that contain network implications. Second, it explores single levels of analysis rather than the multiple levels out of which most networks are comprised. Third, network analysis has employed very little the insights from contemporary complex systems analysis and computer simulations. Foruth, it typically uses descriptive rather than inferential statistics, thus robbing it of the ability to make claims about the larger universe of networks. Finally, almost all the research is static and cross-sectional rather than dynamic. Theories of Communication Networks presents solutions to all five problems. The authors develop a multitheoretical model that relates different social science theories with different network properties. This model is multilevel, providing a network decomposition that applies the various social theories to all network levels: individuals, dyads, triples, groups, and the entire network. The book then establishes a model from the perspective of complex adaptive systems and demonstrates how to use Blanche, an agent-based network computer simulation environment, to generate and test network theories and hypotheses. It presents recent developments in network statistical anlysis, the p* family, which provides a basis for valid multilevel statistical inferences regarding networks. Finally, it shows how to relate communication networks to other networks, thus providing the basis in conjunction with computer simulations to study the emergence of dynamic organizational networks.

Communication --- Interpersonal communication. --- Social interaction. --- Social perception. --- Social aspects. --- Interaction sociale --- Communication interpersonnelle --- Perception sociale --- Aspect social

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This book addresses prediction, mining and analysis of offline characteristics and behaviors from online data and vice versa. Each chapter will focus on a different aspect of virtual worlds to real world prediction e.g., demographics, personality, location, etc. There is a growing body of literature that focuses on the similarities and differences between how people behave in the offline world vs. how they behave in these virtual environments. Data mining has aided in discovering interesting insights with respect to how people behave in these virtual environments.

Internet --- Virtual reality --- Computer games --- Social aspects. --- Social sciences --- Computer Appl. in Social and Behavioral Sciences. --- Data-driven Science, Modeling and Theory Building. --- Methodology of the Social Sciences. --- Mathematics in the Humanities and Social Sciences. --- Data processing. --- Methodology. --- Application software. --- Sociophysics. --- Econophysics. --- Social sciences. --- Mathematics. --- Math --- Science --- Behavioral sciences --- Human sciences --- Sciences, Social --- Social science --- Social studies --- Civilization --- Economics --- Statistical physics --- Mathematical sociology --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Statistical methods

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