Network Science#

As discussed earlier in the course, networks are everywhere!

This week, we will broaden up from learning and social networks to consider a wide range of networks.

Video of Albert-László Barabási, The hidden networks of everything#

Readings#

  • Barabasi, A.-L. (2016). Network Science (1st edition) (Chapter 1). Cambridge University Press.

  • Zweig, K. A. (2016). Graph Theory, Social Network Analysis, and Network Science. In K. A. Zweig (Ed.), Network Analysis Literacy: A Practical Approach to the Analysis of Networks (pp. 23–55). Springer. https://doi.org/10.1007/978-3-7091-0741-6_2

  • [Optional] Borgatti, S. P., Mehra, A., Brass, D. J., & Labianca, G. (2009). Network analysis in the social sciences. Science, 323(5916), 892–895. https://doi.org/10.1126/science.1165821

Lab: Getting started with network data#

As you continue to read about various ways of applying network analysis, follow the Jupyter notebook on the next page to start playing with network data.

This lab activity aims to get you comfortable with the typical process of importing well-structured network data.

In later weeks, we will discuss multiple ways to represent networks and data wrangling that is usually needed for a network analysis project.