| This course will present state-of-the-art research and practice of large social network analysis. It will provide the students with a network-centric view of modern society. This course will adopt a cross-disciplinary approach by studying real-life networks from business, economics, sociology, biology, computer science, physics, and mathematics, etc. It will provide students with essential analyzing and modeling techniques for understanding and extracting information from these important real-life networks. Students will study both the networks’ structure and its dynamic behavior, characterized by these important concepts: like strong and weak ties, community detection, node centrality, positive and negative relationships, giant component, small diameter, power-law distribution and clustering, information cascade, network effects, wisdom of crowds, small-world phenomenon, Page-rank, tipping point, and viral marketing. |
