Social Influence

Diffusion and Contagion

  • What we do is influenced by what others do
  • Network effects
    • Standards, languages, technologies
  • Social constructs
    • Concepts or things have meaning and importance through social
  • Beliefs

Simple contagion

  • Small world networks make simple contagion (like COVID-19) is really hard to stop!
  • Most interventions are network interventions
    • Stopping travel attempts to block “long” ties
    • Social distancing and shelter-in-place attempt to reduce degree
  • The most important people to influence are those with high betweenness centrality

Example

## Warning: Using the `size` aesthetic in this geom was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` in the `default_aes` field and elsewhere instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was generated.

Complex contagion

  • Most communication-related diffusions are complex
    • You don’t change beliefs/behavior just from influence from one other person
  • Complex contagions require multiple ties between groups
    • This is one reason groups can persist in different beliefs

Example

Special People

  • Why is the Mona Lisa the most famous painting in the world?
    • Because there had to be a most famous painting – success begets success (rich-get-richer)

How does this apply to networks?

  • Can we predict who will trigger large-scale information cascades?
    • Not very well
    • If we look in hindsight, a viral tweet seems genius, appropriate, and well-timed
    • There were likely hundreds or thousands of similar tweets
  • Luck + (ever-changing) structure of networks matter more than attributes of information or information spreaders
  • Network position is also closely related to luck!