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Introduction to Network Analysis


Course title

Introduction to Network Analysis.



Drs. Sean Cornelius and Emma Towlson, Center for Complex Network Research, Northeastern University, ,

Sean Cornelius (PhD, Northwestern University, 2014) and Emma Towlson (PhD, University of Cambridge, 2015) are postdoctoral scholars at Northeastern’s Center for Complex Network Research. Sean specializes in the dynamics of networks and networks control, with applications to biological systems. Emma has extensive experience researching brain networks of various kinds, from the structural neuronal level to the macroscopic and functional.


Course language



Course schedule

June 26 to 30: 3:00pm to 6:00pm.



We are surrounded by systems that are hopelessly complex, from the society, a collection of seven billion individuals, to communications systems, integrating billions of devices, from computers to cell phones. Our very existence is rooted in the ability of thousands of genes to work together in a seamless fashion; our thoughts, reasoning, and our ability to comprehend the world surrounding us is hidden in the coherent activity of billions of neurons in our brain. In its simplest form, a network is a set of nodes connected by links. 


Lecture plan

This course is an interdisciplinary introduction to the emerging science of complex networks and their applications. Students will learn about the ongoing research in the field, and ultimately apply their knowledge to conduct their own analysis of a real network data set of their choosing as part of the final project. Topics to be covered include:


  1. The mathematics of networks (Graph Theory).
  2. Random networks and null models.
  3. Basic network measures.
  4. Characterizing large networks.
  5. Data analysis in Python.
  6. Applications to Biology, Sociology, Technology, and other fields. 



Students will be evaluated based on a project, to be presented in the final class, and during the week. They will collect data representing a real network of their choice and analyze it using the network measures and computational tools introduced in class. The goal is to craft a complete “story”: what does Network Science tell us about the system’s organization and function?