Social Network Analysis (SNA) is a powerful and generalizable method that allows insight into the complicated patterns found within social connection data. This repository contains the presentation and demo for an introductory workshop intended for a beginner audience. The session introduces SNA; including how to structure data before building a network, calculating and interpreting basic network statistics, and commonly used tools and technologies. A number of applied examples from across industry and academia are discussed to demonstrate the versatility of SNA. Finally, a hands-on demo will walk through creating, visualizing, and analyzing social networks using industry standard Python packages.
The repository contains the following files:
- Powerpoint presentation (IntroSNA_Share.pptx)
- Annotated Jupyter Notebook Demo (Intro to SNA Demo.ipynb)
- Folder with collection script and data used in Demo (VotingData folder)
The demo notebook walks through 2 examples:
- A simple example of building the student friendship network discussed in the slides
- A real-data example of building a voting network diagram for the 115th (2018) U.S. Senate. The interactive visualization output from this example can be explored here.
