Efficient access to Big Data and the development of related technologies have driven the study of complex social systems. This talk will focus on two aspects of the study of complex social systems: predictability and inequality. For predictability, we will look into the publishing industry through mining New York Times bestsellers and bestselling authors, and develop an algorithm to provide early prediction of book sales. For inequality, first we look into a large-scale investigation of gender underrepresentation in the art world, using various statistical tools and complex networks. And second, we investigate how inequality emerges in information access in a network using network generative models and information propagation simulation.
Xindi obtained obtained a Ph.D. degree from Northeastern in Network Science, working with Prof. Albert-László Barabási and Prof. Tina Eliassi-Rad. Her research projects include network science, computational social science, machine learning and data science. Specifically she is most interested in the predictability and inequalities in complex systems. In the past year, Xindi worked as an Applied Scientist II in Amazon Alexa AI, building machine learning models to make Alexa smarter to retrieve desired results for customers.