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ETH Zurich – Distributed Computing – www.disco.ethz.ch
Chen Avin, Barbara Keller, Zvi Lotker, Claire Mathieu, Yvonne-Anne Pignolet, David Peleg
Homophily and the Glass Ceiling Effect
in Social Networks
Do you notice something?
oo o
o
o
o
o
o
o
What is happening?
The "glass ceiling"... is the
unseen, yet unbreakable barrier
that keeps minorities and
women from rising to the upper
rungs of the corporate ladder,
regardless of their qualifications
or achievements.
Federal Glass Ceiling Commission, US Government (1995)
Unequal Entry Rates
Homophily
The Rich get Richer (Preferential Attachment)
PhD Students and their Advisor
ρ
1-ρ
How does such a Network look like?
r = 0.5, ρ = 0.7
How does such a Network look like?
r = 0.3, ρ = 1
How does such a Network look like?
r = 0.3, ρ = 0
How does such a Network look like?
r = 0.3, ρ = 0.7
Glass Ceiling: How is it defined?
Tail glass ceiling: G(n) exhibits glass ceiling
effect for the red nodes if:
while:
Does this Produce a Glass Ceiling?
r = 0.5, ρ = 0.7
Does this Produce a Glass Ceiling?
r = 0.3, ρ = 1
Does this Produce a Glass Ceiling?
r = 0.3, ρ = 0
Does this Produce a Glass Ceiling?
r = 0.3, ρ= 0.7
Formal Results
Theorem:
Let 0 < r < ½ and 0 < ρ < 1 then G(n, r, ρ) exhibits
a glass ceiling effect (for any starting condition).
Formal Results
Theorem:
G(n, r, ρ) will not have glass ceiling effect in the following
cases:
1. If the rate r = ½ (and for any value of ρ).
2. If ρ = 0 or ρ =1 (and for any value of r).
3. If a new vertex at time t selects its advisor uniformly
at random from all nodes at time t-1
(and for any value of r and ρ).
Proof Overview
1. Fast convergence of sum of degrees of red
nodes in expectation (independent of
starting condition)
2. High probability convergence
3. Power law degree distribution of each gender
PhD and Supervisor Network
PhD and Supervisor Network
1.Definitions for glass celling effect in
networks
2.Simple Mathematical model:
– Unequal entry rate, “rich get richer”, homophily
3.Proof for glass ceiling emergence
– three assumptions → glass ceiling
– any two assumptions → no glass ceiling.
4.Analyzed the DBLP
Summary
Future Work
• Include nodes leaving the network
• Evaluate network with higher percentage of
females
‫רבה‬ ‫תודה‬

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HomophilyGlassCeiling.pptx

  • 1. ETH Zurich – Distributed Computing – www.disco.ethz.ch Chen Avin, Barbara Keller, Zvi Lotker, Claire Mathieu, Yvonne-Anne Pignolet, David Peleg Homophily and the Glass Ceiling Effect in Social Networks
  • 2.
  • 3. Do you notice something? oo o o o o o o o
  • 4.
  • 5. What is happening? The "glass ceiling"... is the unseen, yet unbreakable barrier that keeps minorities and women from rising to the upper rungs of the corporate ladder, regardless of their qualifications or achievements. Federal Glass Ceiling Commission, US Government (1995)
  • 6. Unequal Entry Rates Homophily The Rich get Richer (Preferential Attachment) PhD Students and their Advisor
  • 8.
  • 9. How does such a Network look like? r = 0.5, ρ = 0.7
  • 10. How does such a Network look like? r = 0.3, ρ = 1
  • 11. How does such a Network look like? r = 0.3, ρ = 0
  • 12. How does such a Network look like? r = 0.3, ρ = 0.7
  • 13. Glass Ceiling: How is it defined? Tail glass ceiling: G(n) exhibits glass ceiling effect for the red nodes if: while:
  • 14. Does this Produce a Glass Ceiling? r = 0.5, ρ = 0.7
  • 15. Does this Produce a Glass Ceiling? r = 0.3, ρ = 1
  • 16. Does this Produce a Glass Ceiling? r = 0.3, ρ = 0
  • 17. Does this Produce a Glass Ceiling? r = 0.3, ρ= 0.7
  • 18. Formal Results Theorem: Let 0 < r < ½ and 0 < ρ < 1 then G(n, r, ρ) exhibits a glass ceiling effect (for any starting condition).
  • 19. Formal Results Theorem: G(n, r, ρ) will not have glass ceiling effect in the following cases: 1. If the rate r = ½ (and for any value of ρ). 2. If ρ = 0 or ρ =1 (and for any value of r). 3. If a new vertex at time t selects its advisor uniformly at random from all nodes at time t-1 (and for any value of r and ρ).
  • 20. Proof Overview 1. Fast convergence of sum of degrees of red nodes in expectation (independent of starting condition) 2. High probability convergence 3. Power law degree distribution of each gender
  • 21.
  • 22.
  • 25. 1.Definitions for glass celling effect in networks 2.Simple Mathematical model: – Unequal entry rate, “rich get richer”, homophily 3.Proof for glass ceiling emergence – three assumptions → glass ceiling – any two assumptions → no glass ceiling. 4.Analyzed the DBLP Summary
  • 26. Future Work • Include nodes leaving the network • Evaluate network with higher percentage of females