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This concept is dynamically articulated through computational social science approaches including network and text analysis. Nima Zahedinameghi earned a Ph.D. in sociology from Laval University. He comes to data science from a social science background where he has received both quantitative and theoretical training in the field. His current research agenda revolves around the combined application of social and complex systems theory and formal methods such as agent-based modeling and computational techniques. Methodologically, he is interested in using artificial intelligence for the study of human behavior in large-scale social systems. Nima also has a keen interest in data science as an overarching discipline for conducting interdisciplinary research in different aspects of society, politics, and economics.
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