Social Networks 101 P ROF. J ASON H ARTLINE AND P ROF. N ICOLE I MMORLICA.

Slides:



Advertisements
Similar presentations
1 Stable Matching A Special Case of Stable Marriage.
Advertisements

Blah blah blah. Zoes shark Thanks to the conference artist Phoebe.
The Mathematics Of 1950s Dating: Who wins the battle of the sexes? Great Theoretical Ideas In Computer Science Steven Rudich CS Spring 2003 Lecture.
Piyush Kumar (Lecture 3: Stable Marriage) Welcome to COT5405.
Prof. Swarat Chaudhuri COMP 482: Design and Analysis of Algorithms Spring 2013 Lecture 2.
Marriage, Honesty, & Stability N ICOLE I MMORLICA, N ORTHWESTERN U NIVERSITY.
Tutorial 5 of CSCI2110 Eulerian Path & Hamiltonian Cycle Tutor: Zhou Hong ( 周宏 )
Matching Theory.
Mutual Exclusion By Shiran Mizrahi. Critical Section class Counter { private int value = 1; //counter starts at one public Counter(int c) { //constructor.
Matching problems Toby Walsh NICTA and UNSW. Motivation Agents may express preferences for issues other than a collective decision  Preferences for a.
Social Networks 101 P ROF. J ASON H ARTLINE AND P ROF. N ICOLE I MMORLICA.
The Wife of Bath’s Tale. Medieval Marriage Many medieval marriages were arranged based on financial gains rather than love. Most women didn’t have a choice.
Social Networks 101 P ROF. J ASON H ARTLINE AND P ROF. N ICOLE I MMORLICA.
1 Discrete Structures & Algorithms Graphs and Trees: IV EECE 320.
CSE 421 Algorithms Richard Anderson Lecture 2. Announcements Office Hours –Richard Anderson, CSE 582 Monday, 10:00 – 11:00 Friday, 11:00 – 12:00 –Yiannis.
Lecture 4 CSE 331 Sep 9, Blog posts for lectures Starts from today See Sep 8 post on the blog.
1 Bipartite Matching Polytope, Stable Matching Polytope x1 x2 x3 Lecture 10: Feb 15.
Lecture 8 CSE 331 Sep 17, HW 1 due today Place Q1 and Q2 in separate piles I will not accept HWs after 1:15pm.
Lecture 6 CSE 331 Sep 10, Homeworks HW 1 posted online: see blog/piazza Pickup graded HW 0 in TA OHs.
Chapter 10: Iterative Improvement Simplex Method The Design and Analysis of Algorithms.
The Stable Marriage Problem
MATH AND LOVE G6. ITRODUCE  Only boys can pursue women.  Every girls can only have one boy friend. So do boys.  Every boys and girls has there own.
1 Stable Matching Problem Goal. Given n men and n women, find a "suitable" matching. n Participants rate members of opposite sex. n Each man lists women.
The Mathematics Of Dating and Marriage: Who wins the battle of the sexes? The Mathematics Of Dating and Marriage: Who wins the battle of the sexes? (adapted.
The Mathematics Of 1950’s Dating: Who wins the battle of the sexes? Adapted from a presentation by Stephen Rudich.
결혼문제로 본 조합론.
The Mathematics Of 1950’s Dating: Who wins the battle of the sexes? Presentation by Shuchi Chawla with some modifications.
Section 2.1 “Matching in bipartite graphs” in Graph Theory Handout for reading seminar.
Advanced Algorithms Piyush Kumar (Lecture 1: Introduction) Welcome to COT5405.
Stable Matchings a.k.a. the Stable Marriage Problem
Great Theoretical Ideas in Computer Science.
1 The Stable Marriage Problem Algorithms and Networks 2014/2015 Hans L. Bodlaender Johan M. M. van Rooij.
Marriage and Mathematics Lau Ting Sum Samson Suen Wai.
All Pair Shortest Path IOI/ACM ICPC Training June 2004.
Lecture 23: Stable Marriage ( Based on Lectures of Steven Rudich of CMU and Amit Sahai of Princeton) Shang-Hua Teng.
Stable Matching Lecture 7: Oct 3. Matching A B C DE Boys Girls Today’s goal: to “match” the boys and the girls in a “good” way.
Stable Marriages (Lecture modified from Carnegie Mellon University course Great Theoretical Ideas in Computer Science)
Design & Co-design of Embedded Systems Final Project: “The Match Maker” Second Phase Oral Presentation Safa S. Mahmoodian.
Bipartite Matching. Unweighted Bipartite Matching.
CSE 421 Algorithms Richard Anderson (for Anna Karlin) Winter 2006 Lecture 2.
The Stable Marriage Problem
Great Theoretical Ideas in Computer Science for Some.
Matching Lecture 19: Nov 23.
Fair Shares.
The Mathematics Of 1950’s Dating: Who wins the battle of the sexes? CS Lecture 2.
Graph Algorithms Maximum Flow - Best algorithms [Adapted from R.Solis-Oba]
CSCI 256 Data Structures and Algorithm Analysis Lecture 2 Some slides by Kevin Wayne copyright 2005, Pearson Addison Wesley all rights reserved, and some.
Market Design and Analysis Lecture 2 Lecturer: Ning Chen ( 陈宁 )
Market Design and Analysis Lecture 1 Lecturer: Ning Chen ( 陈宁 )
18.1 CompSci 102 Today’s topics 1950s TV Dating1950s TV Dating.
Algorithms used by CDNs Stable Marriage Algorithm Consistent Hashing.
18.1 CompSci 102 Today’s topics Impaired wanderingImpaired wandering Instant InsanityInstant Insanity 1950s TV Dating1950s TV Dating Final Exam reviewFinal.
Stable marriages Competitive programming and problem solving Yoram Meijaard.
Dating Advice from Mathematics
מתמטיקה בדידה Discrete Math Lecture 12 1 TexPoint fonts used in EMF.
Matching Boys Girls A B C D E
Cybernetica AS & Tartu University
Stable Matching.
The Stable Marriage Problem
The Mathematics Of 1950’s Dating: Who wins the battle of the sexes?
Maximum Flow - Best algorithms
CSE 421: Introduction to Algorithms
The Mathematics Of 1950’s Dating: Who wins The Battle of The Sexes?
The Mathematics Of 1950’s Dating: Who wins the battle of the sexes?
S. Raskhodnikova; based on slides by K. Wayne
Computational Processes II
CSE 421: Introduction to Algorithms
Computational Processes II
Lecture 6 CSE 331 Sep 12, 2011.
Piyush Kumar (Lecture 3: Stable Marriage)
Presentation transcript:

Social Networks 101 P ROF. J ASON H ARTLINE AND P ROF. N ICOLE I MMORLICA

Markets + Romance

Objective Study a simple model for a dating market Study stylized “dating ritual” Observe market’s predictions.

Love, marriage, & bipartite graphs the boys and girls Jake Elwood Curtis Ray Twiggy Claire Jill Holly Holly > Claire > Twiggy > Jill Claire > Jill > Twiggy > Holly Twiggy > Jill > Holly > Claire Holly > Claire > Twiggy > Jill Jake > Elwood > Curtis > Ray Jake > Curtis > Elwood > Ray Ray > Curtis > Elwood > Jake Ray > Jake > Elwood > Curtis

What do markets say on romance? Question A. Do “lasting” marriages always exist? Question B. Are they easy to find? Question C. Do conventional “dating rituals” result in lasting marriages?

What could keep marriages from lasting?

A pair (m,w) is a blocking pair for a matching if m prefers w to his match and w prefers m to her match. When is marriage stable? Jake Elwood Curtis Ray Twiggy Claire Jill Holly Holly > Claire > Twiggy > Jill Claire > Jill > Twiggy > Holly Twiggy > Jill > Holly > Claire Holly > Claire > Twiggy > Jill Jake > Elwood > Curtis > Ray Jake > Curtis > Elwood > Ray Ray > Curtis > Elwood > Jake Ray > Jake > Elwood > Curtis

When is marriage stable? A pair (m,w) is a blocking pair for a matching if m prefers w to his match and w prefers m to her mat c h. A matching is stable if there is no blocking pair.

The (stylized) courtship ritual Jake Elwood Curtis Ray Holly > Claire > Twiggy > Jill Claire > Jill > Twiggy > Holly Twiggy > Jill > Holly > Claire Holly > Claire > Twiggy > Jill Twiggy Claire Jill Holly Jake > Elwood > Curtis > Ray Jake > Curtis > Elwood > Ray Ray > Curtis > Elwood > Jake Ray > Jake > Elwood > Curtis

Facts about Courtship Ritual Fact 1. Courtship ritual terminates. Fact 2. Everyone marries. Fact 3. Resulting marriage is stable. Consequences: Answer A. Yes, stable matchings always exist. Answer B. Yes, stable matchings are easy to find. Answer C. Yes, the courtship ritual works.

Termination The courtship ritual terminates. 1.In each step, someone crosses off a name from their list. 2.Only a finite number of names, so ritual cannot run forever.

Everyone marries Everyone marries. Assume for contradiction: boy B isn’t married. 1.Then B has crossed everyone off his list. 2.So each girl was engaged at some point. 3.But, once a girl is engaged, always engaged. 4.So, all girls are married (to unique boy). 5.But number of girls equals number of boys. 6.So, B must be married. CONTRADICTION!

Stability The resulting matching is stable. Consider boy B and girl G that are not married to each other. 1.Suppose G was crossed off B’s list. Then G prefers husband to B, so won’t elope with B. 2.Suppose G is on B’s list. Then B didn’t propose to G yet, so B prefers wife to G, so won’t elope with G.

Facts about Courtship Ritual Fact 1. Courtship ritual terminates. Fact 2. Everyone marries. Fact 3. Resulting marriage is stable. Consequences: Answer A. Yes, stable matchings always exist. Answer B. Yes, stable matchings are easy to find. Answer C. Yes, the courtship ritual works.

Would you rather? Would you rather be a boy or a girl? (who are better off, the boys or the girls?)

Recall matching from ritual… Jake Elwood Curtis Ray Holly > Claire > Twiggy > Jill Claire > Jill > Twiggy > Holly Twiggy > Jill > Holly > Claire Holly > Claire > Twiggy > Jill Twiggy Claire Jill Holly Jake > Elwood > Curtis > Ray Jake > Curtis > Elwood > Ray Ray > Curtis > Elwood > Jake Ray > Jake > Elwood > Curtis

An alternate universe: girls propose Jake Elwood Curtis Ray Holly > Claire > Twiggy > Jill Claire > Jill > Twiggy > Holly Twiggy > Jill > Holly > Claire Holly > Claire > Twiggy > Jill Twiggy Claire Jill Holly Jake > Elwood > Curtis > Ray Jake > Curtis > Elwood > Ray Ray > Curtis > Elwood > Jake Ray > Jake > Elwood > Curtis

Conclusion: not unique Jake Elwood Curtis Ray Twiggy Claire Jill Holly Holly > Claire > Twiggy > Jill Claire > Jill > Twiggy > Holly Twiggy > Jill > Holly > Claire Holly > Claire > Twiggy > Jill Jake > Elwood > Curtis > Ray Jake > Curtis > Elwood > Ray Ray > Curtis > Elwood > Jake Ray > Jake > Elwood > Curtis

Stable spouses In general, there are many stable marriages. Boy B Girl G Girl G’ A person P is a stable spouse of a person P’ if P is married to P’ in some stable matching.

Boys are happier than girls In boys-propose ritual: 1.Boys marry their most preferred stable wife. 2. Girls get their least preferred stable husband! way

Assume for contradiction: some boy isn’t married to favorite stable spouse. 1.Let B be 1 st boy to lose his favorite stable wife G. 2.Then G must have had a proposal from a boy B’ she preferred to B. 3.Since B’ has not yet crossed off his favorite stable wife, B’ must love G more than any stable wife. 4.But then B’ and G will elope in marriage which matches B to G, contradicting stability of wife G.

Assume for contradiction: some girl G isn’t married to least favorite stable spouse. 1.Let M be the matching from boys-propose ritual where G is matched to B. 2.Let M’ be stable matching where G is matched to least favorite stable husband B’. 3.Then G prefers B to B’ by assumption. 4.But B’s favorite stable wife is G, So B and G prefer each other than spouses in M’. 5.But them M’ is not stable.

But of course … symmetry If girls propose, then they will get their favorite stable husbands.

Conclusions You’ll get a better match if you do the proposing!

Other applications of stable marriage Hospitals Medical Interns Schools Students Servers Requests

Next time Prediction markets.