Most existing social network analysis has focused on networks with only positive links (or unsigned networks). However, in many real-world social systems, relations between two nodes can be represented as networks with both positive and negative links, where negative links can denote foes, distrust, “friended" and “followed" friends, and blocked users. The introduction of negative links in signed networks not only increases the complexity, but also poses tremendous challenges for traditional unsigned network analysis. It is evident that negative links have distinct properties from positive links; and the fundamental principles and theories of signed networks are substantially different from those of unsigned networks. Hence, dedicated efforts are desired for signed networks. In this talk, I will systematically introduce our work on signed social network analysis from foundations to applications, which suggest great opportunities in this new research subfield.
Jiliang Tang is an assistant professor in the computer science and engineering department at Michigan State University since Fall 2016. Before that, he was a research scientist in Yahoo Research and got his PhD from Arizona State University in 2015. He has broad interests in data science and is directing the Data Science and Engineering Lab. He was the recipients of the Best Student Paper Award, the Best Paper Award in KDD2016, the runner up of the Best KDD Dissertation Award in 2015, and the best paper runner up of WSDM2013. He has served as the editors and the organizers in prestigious journals and conferences. He has published his research in highly ranked journals and top conference proceedings, which received thousands of citations and extensive media coverage. More details can be found via https://www.cse.msu.edu/~tangjili/.