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Page 1: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,

An Analysis of One-Dimensional Schelling Segregation

GAUTAM KAMATH, CORNELL UNIVERSITYCHRISTINA BRANDT, STANFORD

UNIVERSITYNICOLE IMMORLICA, NORTHWESTERN

UNIVERSITYROBERT KLEINBERG, CORNELL UNIVERSITY

Page 2: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,

- White

- Black

- Hispanic

- Asian

The New Yorker Hotel

In a one-dimensionalnetwork with local neighborhoods,

segregation exhibits only local effects.

map by Eric Fischer

Goal: Mathematically model andunderstand residential segregation

Page 3: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,
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Start with a randomcoloring of the ring

n = size of ring

Page 5: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,

Happy if at least 50% like-colored

near neighbors.w = window size

Page 6: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,

At each time step, swapposition of two unhappy

individuals of opposite color

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Segregation:run-lengths in

stable configuration

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Local dynamics lead to segregation.• Schelling’s experiment: n = 70, w = 4• Average run length: 12

Schelling’s Experimental Result:

Page 9: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,

The Big Questions

• Is run length a function of n or w? Global vs. local segregation

• If function of w, polynomial vs. exponential?

Page 10: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,

In the perturbed Schelling model, segregation is global and severe. (stable run length: O(n))

Young’s result:

[Young, 2001]

In the unperturbed Schelling model, segregation is local and modest. (stable run length: O(w2))

Our main result (informal):

[Brandt, Immorlica, Kamath, Kleinberg, 2012]

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Working our way up

1. With high probability, process will reach a stable configuration

2. Average run length independent of ring size3. Average run length is modest

Page 12: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,

Techniques

Defn. A firewall is a sequence of w+1 consecutive individuals of the same type.

Claim: Firewalls are stable with respect to the dynamics.

Page 13: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,

Convergence

Theorem. For any fixed window size w, as n grows, the probability that the process reaches a stable configuration converges to 1.

Proof Sketch: 1. With high probability, there exists a firewall in

the initial configuration2. Individual has positive probability of joining a

firewall, and can never leave

Page 14: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,

Working our way up

1. With high probability, process will reach a stable configuration

2. Average run length independent of ring size3. Average run length is modest

Page 15: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,

An easy bound on run length

Theorem. Ave run length in final state is O(2w).Proof.

• Expect to look O(2w) steps before we find a blue firewall in both directions

• Bounds length of a green firewall containing site• Symmetric for a blue firewall containing site

random site

look for blue firewalllook for blue firewall

Page 16: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,

Working our way up

1. With high probability, process will reach a stable configuration

2. Average run length independent of ring size3. Average run length is modest

Page 17: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,

Techniques

1. Define firewall incubators, frequent at initialization.2. Show firewall incubators are likely to become firewalls.

A blue firewall incubator,rich in blue nodes.

A green firewall incubator, rich in green nodes.

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Simulation, n = 1000, w = 10

time t = 0

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time t = 40

Simulation, n = 1000, w = 10

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time t = 80

Simulation, n = 1000, w = 10

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time t = 120

Simulation, n = 1000, w = 10

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time t = 160

Simulation, n = 1000, w = 10

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time t = 260 (final)

Simulation, n = 1000, w = 10

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time t = 160

Simulation, n = 1000, w = 10

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time t = 120

Simulation, n = 1000, w = 10

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time t = 80

Simulation, n = 1000, w = 10

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time t = 40

Simulation, n = 1000, w = 10

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Simulation, n = 1000, w = 10

time t = 0

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time t = 40

Simulation, n = 1000, w = 10

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time t = 80

Simulation, n = 1000, w = 10

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time t = 120

Simulation, n = 1000, w = 10

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time t = 160

Simulation, n = 1000, w = 10

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time t = 260 (final)

Simulation, n = 1000, w = 10

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Four steps to O(w2)

1. Firewall incubators are common

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Firewall Incubators

w sites w sites

Definition. The bias of a site i at time t is the sum of the signs of sites in its neighborhood.

+1 -1 -1 -1-1 +1+1+1 +1 +1 +1 +1

Bias = +3

Page 36: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,

Firewall Incubators

w+1 sites w+1 sites

defender defenderinternalattacker attacker

w sites w sites

left right

Definition. A firewall incubator is a sequence of 3 biased blocks – left defender of length w+1, internal, right defender of length w+1.At least 2w + 2 sites, where the bias of every site is > w1/2.

Page 37: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,

Birth of a Firewall Incubator

Lemma. For any 6w consecutive sites, there’s a constant probability that a uniformly random labeling of sites contains a firewall incubator.Proof Sketch. Random walks + central limit theorem

0

5w1/2

-2w1/2

Page 38: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,

Four steps to O(w2)

1. Firewall incubators are common2. Define an event in which an incubator

deterministically becomes a firewall

Page 39: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,

Lifecycle of a Firewall Incubatorattacker defender

GOOD swap

Page 40: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,

Lifecycle of a Firewall Incubatorattacker defender

BAD swap

Page 41: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,

Lifecycle of a Firewall Incubator

Definition. The transcript is the sign-sequence obtained by associatingeach blue attacker with a +1, each green defender by a -1, and thenlisting signs in reverse-order of when individuals move.

attacker defender

+1 -1 -1+1 +1

5 2 8 6 1swap time:

sign:

transcript: +1, -1, +1, +1, -1

Proposition. If the partial sums of a transcript are non-negative, thenthe firewall incubator becomes a firewall

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Four steps to O(w2)

1. Firewall incubators are common2. There is an event in which an incubator

deterministically becomes a firewall3. Assuming swap order is random, this event

happens

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Lifecycle of a Firewall Incubator

Ballot Theorem. With probability (A – D)/(A + D), all the partial sums of a random permutation of A +1’s and D -1’s are positive.

Firewall incubator definition implies1. A-D ≥ Ɵ(w0.5) (bias condition of incubator)2. A+D ≤ Ɵ(w) (length of attacker + defender)Each defender survives with probability Ω(1/w0.5)Incubator becomes a firewall with probability Ω(1/w)

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Four steps to O(w2)

1. Firewall incubators are common2. There is an event in which an incubator

deterministically becomes a firewall3. Assuming swap order is random, this event

happens4. Swap order is close to random

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Lifecycle of a Firewall Incubator

Swaps are random if there is # unhappy green = # unhappy blue.

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Wormald’s Technique

•We show numbers are approx. equal using Wormald’s theoremTheorem [Wormald]. Under suitable technical conditions, a discrete-time stochastic process is well approximated by the solution of a continuous-time differential equation•Technically non-trivial due to complications with infinite differential equations•Don’t need to solve diff. eq., only exploit symmetry

Page 47: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,

Firewall incubators occur every O(w) locations+

Incubator becomes firewall with probability Ω (1/w)=

Firewalls occur every O(w2) locations

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An better bound on run length

Theorem. Ave run length in final state is O(w2).Proof.

• Expect to look O(w2) steps before we find a blue firewall in both directions

• Bounds length of a green firewall containing site• Symmetric for a blue firewall containing site

random site

look for blue firewalllook for blue firewall

Page 49: An Analysis of One-Dimensional Schelling Segregation G AUTAM K AMATH, C ORNELL U NIVERSITY C HRISTINA B RANDT, S TANFORD U NIVERSITY N ICOLE I MMORLICA,

Summary

•First rigorous analysis of Schelling’s segregation model on one-dimensional ring•Demonstrated that only local, modest segregation occurs–Average run length is independent of n and poly(w)–Subsequent work: Ɵ(w) run length

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Open Questions

• Vary parameters (proportion and number of types, tolerance)

• Study segregation on other graphs– 2D grid


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