Sifting through Measures on Networks: From a Theoretical Framework to an Empirical Guide
In this talk, I will discuss two problems on network data. (1) Measuring tie-strength: Given a set of people and a set of events attended by them, how should we measure connectedness or tie strength between each pair of persons? The underlying assumption is that attendance at mutual events produces an implicit social network between people. I will describe an axiomatic solution to this problem. (2) Measuring similarity between networks: Given two networks (without known node-correspondences), how should we measure similarity between them? This problem occurs frequently in many real-world applications such as transfer learning, re-identification, and change detection. I will present an empirical guide on how to select a network-similarity method, and discuss some promising results based on topological data analysis.