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

Housekeeping

  • Poll Everywhere for discussion questions - add them and vote now
  • Videos + readings on centrality and power
  • How do we measure who is important and influential?
  • Thursday
    • Ego network activity
    • More co-working time

Homework Review

Review

  • What is an “ego network”?
  • What is the “cognitive activation” of a network?
  • Why might SES be related to which networks are activated in stress?

Review

  • What are the benefits of having a dense ego network?
  • What are the benefits of having a sparse ego network?
  • 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?

Discussion Questions

  • Goffman and networks
  • Surveys as questionable data sources
  • How else could we measure networks?
  • Ego vs. nodes

Summary

Thursday class

Debugging

Strategies when R code doesn’t work:

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

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: 1
    • In between: .5

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()