8.3 Analyzing Ego-Centric Networks

In the textbook, the author explores a range of measures that we’ve introduced when studying complete networks, such as density and centrality. This is another chance to examine these concepts even though computing these measures is the same mathematically for complete or ego networks.

In this week, I encourage you to use a complete-network dataset you have in hand (e.g., your own data, demo data we used in earlier weeks, Twitter data I demoed) to:

  • Derive ego-centric networks based on a complete network
  • Conduct basic analysis of ego-centric networks

8.3.1 Track R

This igraph doc is where you can get started. Play with different parameters to see how results could be different.

Additionally, explore ways to extract ego networks from the complete network using the make_ego_graph() function.12

Note: If you haven’t done so yet, please check out the video I made in Week 7. You can add new code dealing with ego-centric networks in to your earlier code. (This is when you’re starting to love R if the past few weeks were a bit rough :).)

8.3.2 Track Gephi

The half-minute video below will give you a sense about steps involved in deriving ego-centric networks from a complete network:

Additionally, there are a number of posts that provide more detailed guidance:

Optional if you’re using Windows:

  1. The sna package provides a function named ego.extract for the same purpose.