Events

Prof. Emma Jingfei Zhang
Goizueta Foundation Term Associate Professor of
Information Systems & Operations Management (ISOM)
Goizueta Business School | Emory University

Many real-world networks contain rich textual information in the edges, such as email networks where an edge between two nodes is an email exchange. The useful textual information carried in the edges is often discarded in most network analyses, resulting in an incomplete view of the relationships between nodes. In this work, we represent each text document as a generalized multi-layer network and introduce a new and flexible preferential latent space network model that can capture how node-layer preferences directly modulate edge probabilities. We establish identifiability conditions for the proposed model and tackle model estimation with a computationally efficient projected gradient descent algorithm. We further derive the non-asymptotic error bound of the estimator from each step of the algorithm. The efficacy of our proposed method is demonstrated through simulations and an analysis of the Enron email network.

Emma Jingfei Zhang is the Goizueta Foundation Term Associate Professor of Information Systems & Operations Management at the Goizueta Business School of Emory University. Dr. Zhang’s research focuses on analyzing large networks, tensors and point processes, with applications in business, public health and biomedical research. Her research has been published in leading journals in statistics, machine learning, and biology, and has been supported by grants from the National Science Foundation. She is currently serving as an associate editor at the Journal of the American Statistical Association, Annals of Applied Statistics, Statistica Sinica, and Journal of Computational and Graphical Statistics.