Week 5 - Ego Networks

Dad Joke

Bro, can you pass me that leaflet?

Brochure.

Self Reflections and feedback

• Make sure to get them in
• Overall, things are going well
• Please give feedback on the Google Form

Housekeeping

• Videos + readings on centrality and power
• How do we measure who is important and influential?
• AI assignment next week
• Thursday
  • Ego network activity
  • More co-working time

Debugging

Strategies when R code doesn’t work:

• Simplify
• print()
• ChatGPT
• Google!
• Friends

Homework Review

Review

• What is an “ego network”?
• What are the benefits of having a dense ego network?
• What are the benefits of having a sparse ego network?

Dense Network Example

Sparse Network Example

Review

• What are some reasons that you think friendship can be asymmetrical?
• Is there such thing as a “true” social network? How could we find it out?
• What are some ways that our perceptions of a network could influence our behaviors?

• Different perception of “friendship”
• Different cognitive activation (who comes to mind)
• Ambition / social status

Break Time

Review

• What is the difference between a potential network, an activated network, and a mobilized network?
• Why might SES be related to which networks are activated under job loss threat?

• Even wider network may not have resources
• Different types of work may require different types of networks
• Higher SES have greater time / money / energy to reach out to more distant connections
• Distant connections respond differently based on SES of asker

Discussion Questions

• What are the consequences of relying on self-reported network data when people may misunderstand who is actually part of their support network?
• Why might personal network sizes differ based on race?
• If dense and family-centered social networks are typically the foundation of most social networks, are social networks naturally structured to limit the spread of new ideas and social change?

Summary

Thursday class

Ego Network Activity

What do our ego networks look like?

• From time to time, most people discuss important matters with other people. Looking back over the last 6 months, who are the people with whom you discussed matters important to you?

Making Connections

• Make an edgelist for each connection, with tie strength of:
  • Total strangers: 0
  • Especially close: 2
  • In between: 1

Write attributes of your connections to a node attribute file

• Sex
• Education (years of education)
• Race
• Age
• Kin or non-kin (are they related to you?)

Calculate your statistics

• Network size
• Kin network size
• Non-kin network size
• Density
• Age heterogeneity
• Education heterogeneity
• Race heterogeneity
• Sex heterogeneity (proportion in majority)

Importing and visualizing in R

• Remember graph_from_data_frame()