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Center for Nonlinear Studies |
Research on human dynamics and computational social science has been revolutionized by new data taken from online social networks. These modern datasets capture activity patterns across very large populations. Using these records, new results have been discovered and existing hypotheses have been tested. But what is the fundamental limit of social information stored in these data? These data also have sampling biases and other issues that make uncertainty quantification crucial. Along these lines, I will discuss current projects related to inferring hidden structure in partially observed networks and using large-scale Twitter data to estimate how information is stored and flows through social networks.
Host: Thomas McAndrew