Thanks for joining this workshop! ;)
Hi all, the recording for this workshop has been uploaded to Box. https://policefoundation.box.com/s/m869rs1lq38zgo3ufuoi4woqbekk8uxw
This workshop aims at providing a theoretical and empirical introduction to network science and its applications in social sciences. We will talk about:
- What are networks? What are the ingredients of a network?
- How to understand/describe a network? What are the positional measurements of a node? What's the local structure? How to summary the global metrics of a network.
- How to model social networks?
We will practice:
- How to construct data for network analysis?
- How to conduct descriptive network analysis?
In a nutshell, this workshop will give you some fundamental flavors of network science and wants to be your first network science crash course. We won't cover these topics in this workshop:
- Statistical inference of a network
- Debugging your code of SNA
- Visualization of the networks
There is no prior knowledge needed for this workshop, but some basic knowledge of Python will be helpful.
I have referenced the following materials during the creation of this workshop (if not cited specifically in different sections):
- Jackson, M. O. (2008). Social and Economic Networks. Princeton University Press. https://doi.org/10.2307/j.ctvcm4gh1
- Network Science by Albert-László Barabási. (n.d.). Retrieved June 10, 2021, from http://networksciencebook.com/
- Leonid Zhukov. (2021, January 14). Lecture1. Introduction to Network Science. https://www.youtube.com/watch?v=1T5-BG6yngM
- Du, D. (n.d.). Social Network Analysis: Lecture 3-Network Characteristics. 57.
- Eric Ma. (n.d.). Network Analysis Made Simple. Retrieved June 10, 2021, from https://ericmjl.github.io/Network-Analysis-Made-Simple/
- Horton, B. S. B., Daniel T. Kaplan, and Nicholas J. (n.d.). Chapter 20 Network science | Modern Data Science with R. Retrieved June 10, 2021, from https://mdsr-book.github.io/mdsr2e/