The treeness of a directed acyclic graph (DAG) describes how close the graph is to a tree. Citation networks are by nature DAGs thus they are perfect research objects to study network treeness as well as its evolution over time. The treeness of a citation network can be affected by many factors such as the number of citations in each paper and how papers cite others.
In this thesis, the student will read and study related literatures on network treeness  and generative network models. The student will measure the treeness of citation networks (already extracted) in different time periods using existing methods. The student will then propose a generative model to reproduce the evolution of network treeness as well as other properties of real networks such as heavy-tailed degree distributions, and analyse the properties of the model empirically and (preferably) analytically.
- Python or Matlab/Octave;
- Knowledge in graph theory or network theory.
 B. Corominas-Murtra, J. Goñi, R. V. Solé, and C. Rodrı́guez-Caso, “On the origins of hierarchy in complex networks,” Proceedings of the National Academy of Sciences, vol. 110, no. 33, pp. 13 316–13 321, 2013.