the old boy (and girl) network: social network formation on university campuses

The Old Boy (and Girl) Network: The Old Boy (and Girl) Network:

Social Network Formation Social Network Formation

on University Campuseson University Campuses

Adi Mayer and Steve PullerAdi Mayer and Steve Puller

Texas A&MTexas A&M

Motivation to StudyMotivation to Study Social Networks in Higher Education Social Networks in Higher Education

Social networks determine “peer effects” Social networks determine “peer effects” in collegein college

Sacerdote (2001), Zimmerman (2003), Winston and Sacerdote (2001), Zimmerman (2003), Winston and Zimmerman (2003), Kremer and Levy (2003), Stinebrickner Zimmerman (2003), Kremer and Levy (2003), Stinebrickner & Stinebrickner (2005), …& Stinebrickner (2005), …

Does race affect social interaction / are Does race affect social interaction / are universities “really” integrated?universities “really” integrated?

Sacerdote & Marmaros (2006)Sacerdote & Marmaros (2006)

Information transmissionInformation transmission Granovetter’s “Strength of Weak Ties”Granovetter’s “Strength of Weak Ties”

Motivation: Motivation: Role of Social Networks in Labor Role of Social Networks in Labor

MarketMarket Social Connections are important for job search:Social Connections are important for job search:

““While the frequency of alternative job-finding methods While the frequency of alternative job-finding methods varies somewhat by sex and occupation, the following varies somewhat by sex and occupation, the following generalization seems fair: generalization seems fair: approximately approximately 50%50% of all of all workers currently employed found their jobs workers currently employed found their jobs through friends and relativesthrough friends and relatives” ” (Montgomery 1991)(Montgomery 1991)

Determination of Wages / EmploymentDetermination of Wages / Employment Job search through social networks generates:Job search through social networks generates:

positively correlated employment across agents and positively correlated employment across agents and time time

positive duration dependence of unemploymentpositive duration dependence of unemployment social networks can generate inequality between two social networks can generate inequality between two

otherwise equivalent groupsotherwise equivalent groups

Calvo-Armengol and Jackson (2004), Pellizarri (2004), Ioannides and Calvo-Armengol and Jackson (2004), Pellizarri (2004), Ioannides and Soetevent (2006), Arrow and Borzekowski (2004)Soetevent (2006), Arrow and Borzekowski (2004)

1) Document structure and segmentation in social network at 10 universities

For one university:

2) Reduced-form description of factors that predict social connections between any two students

3) Explicit model of network formation with counterfactual experiments

Empirical Approach In This Paper:Empirical Approach In This Paper:

What determines the formation of What determines the formation of social networks?social networks?

Social network

Preferences / Tastes

Environment

Do individuals want to be friends?

Do individuals have contact?


Social network

Preferences / Taste Environment

•Race

•Parental background

•Political orientation

•Abilities

•Composition of student body

•Curriculum

•Dorm assignment

•Clubs / Activities


Social network

Preferences / Taste Environment

•Race

•Parental background

•Political orientation

•Abilities

•Composition of student body

•Curriculum

•Dorm assignment

•Clubs / Activities

Policy Instrume

nts

Model of Network formationModel of Network formation

Simulate NetworkSimulate Network

Stage 1: Students meet with probability varying in institutional Stage 1: Students meet with probability varying in institutional

features (e.g. same dorm)features (e.g. same dorm)

Stage 2: Conditional upon meeting, students form friendships Stage 2: Conditional upon meeting, students form friendships

based upon tastes for observable characteristicsbased upon tastes for observable characteristics

Stage 3: Students meet friends of friends with some probability, Stage 3: Students meet friends of friends with some probability,

and again may form friendshipsand again may form friendships

Calibrate parameters of model so simulated network resembles actual Calibrate parameters of model so simulated network resembles actual

networknetwork

Perform Counterfactual ExperimentsPerform Counterfactual Experiments

““Turn off” institutional effects and make all meeting randomTurn off” institutional effects and make all meeting random

““Turn off” tastes and make all “liking” randomTurn off” tastes and make all “liking” random

X-Percent Rule – add more students with specific characteristicsX-Percent Rule – add more students with specific characteristics

Policy

Instruments

Preferences

Preview of ResultsPreview of Results

University social networks exhibit standard features University social networks exhibit standard features

of social networksof social networks

E.g. ClusteringE.g. Clustering

Networks exhibit only modest segmentation in some Networks exhibit only modest segmentation in some

dimensions (ability, parental education, political dimensions (ability, parental education, political

orientation), but substantial segmentation by raceorientation), but substantial segmentation by race

University policies have very limited ability to University policies have very limited ability to

reduce segmentation by racereduce segmentation by race

DataData

From facebook.comFrom facebook.com 10 universities in Texas10 universities in Texas

Texas A&M registrarTexas A&M registrar Additional administrative dataAdditional administrative data

www.facebook.comwww.facebook.com

Online student social network directory for Online student social network directory for each universityeach university

Need official University e-mail to sign upNeed official University e-mail to sign up

Started on February 4, 2004 at HarvardStarted on February 4, 2004 at Harvard

By July 2006, 7By July 2006, 7thth most visited website in US most visited website in US

DataData From facebook.comFrom facebook.com

All student profiles as of 1/17/05 for 10 universities in All student profiles as of 1/17/05 for 10 universities in TexasTexas

65,104 undergraduates65,104 undergraduates (Self-reported) Demographics: year, birthdate, gender, (Self-reported) Demographics: year, birthdate, gender,

high school, hometown, major, current courses, dating high school, hometown, major, current courses, dating status, residence hall, political orientation, jobs, hobbiesstatus, residence hall, political orientation, jobs, hobbies

Social network: links to friends at own-school & other Social network: links to friends at own-school & other schools schools

Race – we classify based upon picturesRace – we classify based upon pictures

Texas A&M registrar:Texas A&M registrar: Race, College performance (GPA), High school Race, College performance (GPA), High school

performance (SAT, class rank), Parental characteristics performance (SAT, class rank), Parental characteristics (income, parents’ education), College activities(income, parents’ education), College activities

The 10 UniversitiesThe 10 Universities

UniversityUniversityUndergradUndergrad EnrollmentEnrollment

FacebookFacebooksamplesample

Fraction in Fraction in FacebookFacebook

RiceRice 2,9332,933 2,3542,354 0.800.80

U TexasU Texas 36,47336,473 14,72814,728 0.400.40

Texas A&MTexas A&M 35,60535,605 15,79715,797 0.440.44

BaylorBaylor 11,52111,521 7,0087,008 0.610.61

Texas TechTexas Tech 23,32923,329 7,2197,219 0.310.31

Texas ChristianTexas Christian 7,0247,024 3,6783,678 0.520.52

SMUSMU 6,0906,090 3,4963,496 0.570.57

U North TexasU North Texas 24,27424,274 4,4744,474 0.180.18

UT ArlingtonUT Arlington 18,17618,176 1,4421,442 0.080.08

Texas StateTexas State 22,40222,402 4,9084,908 0.220.22

Texas A&MTexas A&MStudents In Students In FacebookFacebook

Overall Overall Student Student

PopulationPopulation

GPRGPR 2.952.95 2.932.93

SATSAT 11681168 11521152

High School %ile Class RankHigh School %ile Class Rank 86.586.5 86.086.0

Texas ResidentTexas Resident 97.4%97.4% 97.4%97.4%

FemaleFemale 55.2%55.2% 50.6%50.6%

In a GreekIn a Greek 14.3%14.3% 11.6%11.6%

Lives in a dormLives in a dorm 41.1%41.1% 33.7%33.7%

AthleteAthlete 2.5%2.5% 2.5%2.5%

FreshmanFreshman 27%27% 22%22%

SophomoreSophomore 27%27% 22%22%

JuniorJunior 26%26% 26%26%

SeniorSenior 20%20% 29%29%

WhiteWhite 81.8%81.8% 80.5%80.5%

HispanicHispanic 11.4%11.4% 12.0%12.0%

AsianAsian 4.0%4.0% 3.8%3.8%

BlackBlack 2.3%2.3% 2.9%2.9%

Father College DegreeFather College Degree 61%61% 58%58%

Mother College DegreeMother College Degree 54%54% 51%51%

Household Income < $40,000Household Income < $40,000 14%14% 17%17%

Household Income > $80,000Household Income > $80,000 53%53% 48%48%

Segmentation by Race (Table 5)Segmentation by Race (Table 5) Relative probability of friendship Relative probability of friendship

Pair of:Pair of: RiceRice BaylorBaylorTexasTexasA&MA&M U TexasU Texas

White/Hisp & White/HWhite/Hisp & White/H 1.031.03 1.101.10 1.011.01 1.121.12

White/Hisp & AsianWhite/Hisp & Asian 0.790.79 0.430.43 0.740.74 0.420.42

White/Hisp & BlackWhite/Hisp & Black 0.870.87 0.410.41 0.770.77 0.560.56

Asian & AsianAsian & Asian 2.412.41 4.244.24 7.427.42 4.134.13

Asian & BlackAsian & Black 0.920.92 0.520.52 1.011.01 0.540.54

Black & BlackBlack & Black 5.125.12 5.995.99 16.5416.54 13.1313.13

Any two studentsAny two students 11 11 11 11

Number of pairs of blacks who are friends

Total number of pairs of blacksRelative Probability of Friendship (black&black) = .

Number of pairs of any students who are friends

Total number of any pairs

RiceRice BaylorBaylorTexas Texas A&MA&M U TexasU Texas

Fraction of Students White/HispFraction of Students White/Hisp 0.820.82 0.910.91 0.960.96 0.850.85

Fraction Friends of Whites/Hisp who are Fraction Friends of Whites/Hisp who are White/HispWhite/Hisp 0.850.85 0.960.96 0.970.97 0.930.93

Fraction of Students AsianFraction of Students Asian 0.130.13 0.030.03 0.020.02 0.130.13

Fraction Friends of Asians who are AsianFraction Friends of Asians who are Asian 0.300.30 0.250.25 0.160.16 0.580.58

Fraction of Students BlackFraction of Students Black 0.050.05 0.060.06 0.020.02 0.020.02

Fraction Friends of Blacks who are BlackFraction Friends of Blacks who are Black 0.250.25 0.470.47 0.270.27 0.380.38

Fraction black friends of black student

Relative Probability of Friendship (black&black) * (share of blacks in population)

Segmentation by Race (Table 5)Segmentation by Race (Table 5) “Absolute” Segmentation “Absolute” Segmentation

Segmentation by Political Segmentation by Political Orientation (Table 6)Orientation (Table 6)

RiceRice BaylorBaylorTexas Texas A&MA&M

U U TexasTexas

Fraction of Students LiberalFraction of Students Liberal 0.320.32 0.080.08 0.060.06 0.230.23

Fraction Friends of Lib. who are Lib.Fraction Friends of Lib. who are Lib. 0.380.38 0.120.12 0.100.10 0.290.29

Fraction of Students ConservativeFraction of Students Conservative 0.150.15 0.470.47 0.540.54 0.230.23

Fraction Fraction FriendsFriends of Cons. who are Cons.of Cons. who are Cons. 0.210.21 0.580.58 0.630.63 0.390.39

Pair of:Pair of: Relative probability of friendship Relative probability of friendship

Liberal & LiberalLiberal & Liberal 1.221.22 1.131.13 1.281.28 1.061.06

Liberal & ConservativeLiberal & Conservative 0.860.86 0.590.59 0.690.69 0.750.75

Conservative & ConservativeConservative & Conservative 1.351.35 1.411.41 1.281.28 2.172.17

Any two studentsAny two students 11 11 11 11

Segmentation by Major (Table 6)Segmentation by Major (Table 6)


Fraction of Students in Same Major Fraction of Students in Same Major if Friends Randomif Friends Random 0.040.04 0.020.02 0.020.02 0.020.02

Fraction of Students in Same MajorFraction of Students in Same Major 0.080.08 0.060.06 0.070.07 0.080.08

Structure of Networks (Table 3)Structure of Networks (Table 3)


Avg. Number of FriendsAvg. Number of Friends 50.850.8 59.859.8 41.141.1 39.539.5

Variance of # FriendsVariance of # Friends 31.931.9 50.850.8 38.438.4 36.536.5

Skewness of # FriendsSkewness of # Friends 1.061.06 1.741.74 2.062.06 2.012.01

Cluster CoefficientCluster Coefficient 0.240.24 0.190.19 0.170.17 0.200.20

Cluster Coefficient ConservativesCluster Coefficient Conservatives 0.280.28 0.210.21 0.180.18 0.240.24

Cluster Coefficient LiberalsCluster Coefficient Liberals 0.240.24 0.160.16 0.140.14 0.190.19

Cluster Coefficient BlacksCluster Coefficient Blacks 0.440.44 0.300.30 0.320.32 0.370.37

Cluster Coefficient AsiansCluster Coefficient Asians 0.310.31 0.300.30 0.260.26 0.250.25

Avg. Degrees of SeparationAvg. Degrees of Separation 2.302.30 2.622.62 2.952.95 3.003.00

Rest of Paper: Texas A&M Rest of Paper: Texas A&M onlyonly

, , for all ij i j ijFriends f X X i j

7,719 students

N*(N-1)/2 = 29,787,621 pairs

0.34 % of all pairs are friends

Linear probability modelLinear probability model

Sample: All pairs of students in facebook that are matched to TAMU records and we observe all

characteristics.

Linear probability modelLinear probability model

Regress Friends Y/N onRegress Friends Y/N on

Race (e.g. White-White, White-Black, etc.)Race (e.g. White-White, White-Black, etc.) High School, Cohort, GenderHigh School, Cohort, Gender Family BackgroundFamily Background Dorm, AcademicDorm, Academic AbilityAbility ActivitiesActivities

Predictors of friendship (Table 8)Predictors of friendship (Table 8)

RR22

RaceRace 0.00060.0006

High School, Age, High School, Age, GenderGender 0.02930.0293

Family BackgroundFamily Background 0.00010.0001

Dorm, AcademicDorm, Academic 0.00330.0033

AbilityAbility 0.00010.0001

ActivitiesActivities 0.00320.0032

All CovariatesAll Covariates 0.03600.0360

Predictors of friendship:Predictors of friendship: Dorm /AcademicsDorm /Academics

Only Only Dorm, AcademicDorm, Academic All CovariatesAll Covariates

CoefCoef CoefCoef

ConstantConstant 0.0028*0.0028* 0.0028*0.0028*

Same DormSame Dorm 0.0426*0.0426* 0.0407*0.0407*

Same MajorSame Major 0.0038*0.0038* 0.0030*0.0030*

Same College Same College 0.0018*0.0018* 0.0016*0.0016*

R2= 0.0033

Predictors of friendship: Predictors of friendship: ActivitiesActivities

Only activitiesOnly activities All CovariatesAll Covariates

CoefCoef CoefCoef


Both are AthletesBoth are Athletes 0.0649*0.0649* 0.0635*0.0635*

Both in Corps of CadetsBoth in Corps of Cadets 0.0536*0.0536* 0.0428*0.0428*

Both are GreekBoth are Greek 0.0192*0.0192* 0.0188*0.0188*

One is GreekOne is Greek -0.0003*-0.0003* -0.0003*-0.0003*

One is AthleteOne is Athlete -0.0003-0.0003 -0.0003-0.0003

One in Corps of CadetsOne in Corps of Cadets -0.0005-0.0005 -0.0004-0.0004

R2= 0.0032

Predictors of friendship: Predictors of friendship: RaceRace

Only RaceOnly Race All CovariatesAll Covariates

CoefficientCoefficient CoefficientCoefficient


Both BlackBoth Black 0.0562*0.0562* 0.0542*0.0542*

Both AsianBoth Asian 0.0132*0.0132* 0.0126*0.0126*

Both HispanicBoth Hispanic 0.0028*0.0028* 0.0027*0.0027*

Hispanic - BlackHispanic - Black 0.00110.0011 0.00100.0010

Both WhiteBoth White 0.0011*0.0011* 0.00090.0009

Asian - BlackAsian - Black 0.00080.0008 0.00100.0010

Hispanic - AsianHispanic - Asian 0.00020.0002 0.00050.0005

White - HispanicWhite - Hispanic 0.00010.0001 0.00030.0003

White - BlackWhite - Black -0.0001-0.0001 -0.0002-0.0002

White - AsianWhite - Asian -0.0002-0.0002 -0.0002-0.0002R2= 0.0006

Baseline Probability of friendship = 0.34 percentBaseline Probability of friendship = 0.34 percent

Effect of common friends? (Table Effect of common friends? (Table 9)9)

# of common friends# of common friends ---- 0.0298*0.0298*

ConstantConstant 0.0028*0.0028* -0.0003-0.0003

Both BlackBoth Black 0.0542*0.0542* 0.0151*0.0151*

Both AsianBoth Asian 0.0126*0.0126* 0.0071*0.0071*

Both HispanicBoth Hispanic 0.0027*0.0027* 0.0013*0.0013*

Same High SchoolSame High School 0.1859*0.1859* 0.1379*0.1379*

Same Year in CollegeSame Year in College 0.0010*0.0010* 0.0012*0.0012*

Same GenderSame Gender 0.00000.0000 -0.0005*-0.0005*

Same DormSame Dorm 0.0407*0.0407* 0.0214*0.0214*

Same MajorSame Major 0.0030*0.0030* 0.0024*0.0024*

Both are AthletesBoth are Athletes 0.0635*0.0635* 0.0111*0.0111*

Both are GreekBoth are Greek 0.0188*0.0188* -0.0083*-0.0083*

RR22 0.03600.0360 0.24560.2456Note: all covariates included but not reportedNote: all covariates included but not reported

Endogenous effects through friends of friendsEndogenous effects through friends of friends

Friends of friends matterFriends of friends matter

Magnification of exogenous network Magnification of exogenous network determinatesdeterminates

Simple prediction based on reduced Simple prediction based on reduced from estimation misleadingfrom estimation misleading

Model network formationModel network formation

A model of network formationA model of network formation

• Understand process and Understand process and determinants determinants .. of network of network formationformation

- Meeting vs. TasteMeeting vs. Taste

- Friends of friendsFriends of friends

• Generate counterfactualsGenerate counterfactuals

• Policy evaluationPolicy evaluation


Random Graph Theory Random Graph Theory - cannot explain network features like clusteredness- cannot explain network features like clusteredness

Jackson & Rogers (2005)Jackson & Rogers (2005) Random Meeting & SearchRandom Meeting & Search

- Generates network features- Generates network features- No preferences- No preferences- No institutions / environmental differences - No institutions / environmental differences

We add: We add: (1) environmental differences (1) environmental differences

(2) preferences that determine friendship (2) preferences that determine friendship conditional on conditional on meeting meeting


Observe features of real networkObserve features of real network

Simulate network model for set of parametersSimulate network model for set of parameters

Calculate features of simulated network Calculate features of simulated network

Pick parameters so that features of simulated Pick parameters so that features of simulated

and actual network are as similar as possibleand actual network are as similar as possible

Graph Theoretic Description of Graph Theoretic Description of NetworkNetwork

nn students students

gg is is nn x x nn friendship matrixfriendship matrix

iff iff i,ji,j are friends are friends

otherwiseotherwise

( , ) 1g i j

( , ) 0g i j

Network formationNetwork formation

Initially Initially g=0g=0

1) Meet random students1) Meet random students Like each other? Like each other?

Yes => Yes => ggijij=1=1

2) Meet students in same 2) Meet students in same environmentenvironment Like each other?Like each other?


3) Meet friends of friends3) Meet friends of friends Like each other?Like each other?


1) Random

3) Fr of Fr

2) Environment


Random MeetingRandom Meeting

Each student meets each other student with probabilityEach student meets each other student with probability ppinitinit

Meet students from same environmentMeet students from same environment

• Meet other students in same college with probability Meet other students in same college with probability ppicollicoll • Each student in same cohort with probability Each student in same cohort with probability ppYEARYEAR

• Each other student in same dorm with probability Each other student in same dorm with probability ppDORMDORM

Meet friends of friendsMeet friends of friends

• Each student Each student ii meets all friends of their friends ( meets all friends of their friends (ggikik=1 and =1 and ggkjkj=1) =1)

with probability with probability ppfrofrfrofr

• Repeated Repeated SS times times


Friendship formation conditional on meetingFriendship formation conditional on meeting

• Two students who met become friends if:Two students who met become friends if:

g(i,j)g(i,j) = = II(U(Uijij(.) (.) ≥≥ c cii)·)· I I (U (Ujiji (.) (.)≥ ≥ ccjj))

≡ ≡ II ( ( f f ((XXii,,XXjj,,uuijij;β ;β ) > 0) ) > 0)

where where UUijij = utility to = utility to ii of being friends with of being friends with jj

cci = marginal cost of friendship to = marginal cost of friendship to student student ii

XX = = observable characteristics observable characteristics u =u = unobservable characteristics unobservable characteristics


Two students i,j who met become friends if: , , 0 i j ijf X X u

0

_

, ,

_ _ _

1

1200

i j ij

WW i j BB i j

HH i j AA i j

par edu i j

cons i i

skill i

f X X u

I race race white I race race black

I race race hispanic I race race asian

I parent edu parent edu both coll

I conservative conservative

I SAT

& 1200j ijSAT u

Key AssumptionsKey Assumptions Unobserved tastes are uncorrelated with Unobserved tastes are uncorrelated with

institutional meeting channelsinstitutional meeting channels e.g. No taste for other engineering majorse.g. No taste for other engineering majors

Unobserved determinants of meeting are Unobserved determinants of meeting are uncorrelated with observable taste characteristicsuncorrelated with observable taste characteristics e.g. No Black/Hispanic Student Associatione.g. No Black/Hispanic Student Association

Assessing validity from reduced-form regressions:Assessing validity from reduced-form regressions: Coefficients of College/Cohort/Dorm are robust to Coefficients of College/Cohort/Dorm are robust to

inclusion of covariates on Race/Family inclusion of covariates on Race/Family Background/AbilityBackground/Ability

Coefficients of Race/Family Background/Ability are Coefficients of Race/Family Background/Ability are robust to inclusion of College/Cohort/Dormrobust to inclusion of College/Cohort/Dorm

Model FitModel Fit

Moments Entering CalibrationSample of 1930

StudentsFull Model Simulation

Average # of Friends 6.42 6.42

Variance of # of Friends 6.44 6.27

Skewness of # of Friends 1.82 1.82

Cluster Coefficient 0.15 0.16

Fraction from Same Year 0.44 0.44

Fraction from Same College 0.22 0.22

Fraction from Same Dorm 0.08 0.07

Fraction White Friends of Whites 0.87 0.85

Fraction Hispanic Friends of Hispanics 0.21 0.22

Fraction Asian Friends of Asians 0.15 0.14

Fraction Black Friends of Blacks 0.32 0.33

Fraction Hi SAT Score Friends of Hi SAT 0.49 0.49

Fraction Friends of Same Parental Education 0.53 0.53

Fraction Conservative Friends of Conservative 0.62 0.62

Counterfactual ExperimentsCounterfactual Experiments

Simulate Simulate counterfactual counterfactual network changing…network changing… Institutions that affect Institutions that affect

meeting probabilitymeeting probability Preferences for Preferences for

friends with specific friends with specific characteristicscharacteristics

Friend of friends Friend of friends meeting channelmeeting channel

Random

Fr of Fr

Instit.


Simulate Simulate counterfactual counterfactual network changing…network changing… Institutions that Institutions that

affect meeting affect meeting probabilityprobability

Preferences for friends Preferences for friends with specific with specific characteristicscharacteristics


Random

Fr of Fr

Instit.


Simulate Simulate counterfactual counterfactual network changing…network changing… Institutions that affect Institutions that affect

meeting probabilitymeeting probability Preferences for Preferences for

friends with specific friends with specific characteristicscharacteristics


Random

Fr of Fr

Instit.

Counterfactuals: Counterfactuals: MeetingMeeting

Random

Fr of Fr

Instit.

Random

Fr of Fr

Instit.

Moments Entering CalibrationFull Model Simulation

Completely Random Friends

Full Model without

friends of friends

Random Meeting

Average # of Friends 6.42 6.41 6.42 6.41

Variance of # of Friends 6.27 2.52 2.96 5.56

Skewness of # of Friends 1.82 0.39 0.69 1.58

Cluster Coefficient 0.16 0.00 0.01 0.17

Fraction from Same Year 0.44 0.25 0.59 0.25

Fraction from Same College 0.22 0.13 0.31 0.13

Fraction from Same Dorm 0.07 0.01 0.14 0.01

Fraction White Friends of Whites 0.85 0.82 0.85 0.85

Fraction Hispanic Friends of Hispanics 0.22 0.12 0.23 0.22

Fraction Asian Friends of Asians 0.14 0.04 0.14 0.14

Fraction Black Friends of Blacks 0.33 0.02 0.22 0.28

Fraction Hi SAT Score Friends of Hi SAT 0.49 0.39 0.47 0.47

Fraction Friends of Same Parental Edu 0.53 0.44 0.50 0.52

Fraction Conservative Friends of Cons. 0.62 0.52 0.59 0.61

Random

Fr of Fr

Instit.Random

Fr of Fr

Instit.

Counterfactuals: PreferencesCounterfactuals: PreferencesRandom

Fr of Fr

Instit.


Random Meeting

No Preferences

Average # of Friends 6.42 6.41 6.42

Variance of # of Friends 6.27 5.56 5.77

Skewness of # of Friends 1.82 1.58 1.56

Cluster Coefficient 0.16 0.17 0.16

Fraction from Same Year 0.44 0.25 0.44

Fraction from Same College 0.22 0.13 0.21

Fraction from Same Dorm 0.07 0.01 0.07

Fraction White Friends of Whites 0.85 0.85 0.82

Fraction Hispanic Friends of Hispanics 0.22 0.22 0.12

Fraction Asian Friends of Asians 0.14 0.14 0.03

Fraction Black Friends of Blacks 0.33 0.28 0.02

Fraction Hi SAT Score Friends of Hi SAT 0.49 0.47 0.41

Fraction Friends of Same Parental Education 0.53 0.52 0.45

Fraction Conservative Friends of Conservative 0.62 0.61 0.53

Random

Fr of Fr

Instit. Random

Fr of Fr

Instit.

Counterfactuals: Double Hispanic StudentsCounterfactuals: Double Hispanic Students



Affirmative Action, double

hispanics







Fraction from Same Dorm 0.07 0.01 0.08








Counterfactuals: Introduction to MinoritiesCounterfactuals: Introduction to Minorities



Introduction to students of different race







Fraction from Sam Dorm 0.07 0.01 0.06








Policy = introduce each white to 1% of minorities Policy = introduce each white to 1% of minorities and each minority to 1% of whitesand each minority to 1% of whites

CounterfactualsCounterfactuals Environment has little influence on Environment has little influence on

segmentation by race, ability, backgroundsegmentation by race, ability, background

Affirmative action increases absolute Affirmative action increases absolute segregation of minority, but exposes more segregation of minority, but exposes more white students to minority studentswhite students to minority students

Introduction - small effect on absolute Introduction - small effect on absolute segregation, increases exposure of whites segregation, increases exposure of whites to minority students.to minority students.

ConclusionConclusion

Social networks at universities are Social networks at universities are

segmentedsegmented

Social networks at universities exhibit Social networks at universities exhibit

classic characteristicsclassic characteristics

Limited potential for policies that make Limited potential for policies that make

encounters more randomencounters more random

Other Future Research PossibilitiesOther Future Research Possibilities

Measure “peer effects” on educational Measure “peer effects” on educational outcomesoutcomes Grades (data for TAMU)Grades (data for TAMU) First jobs (TAMU students report at graduation)First jobs (TAMU students report at graduation)

Peer effects in high schoolPeer effects in high school Analyze effects of “school splits” along Analyze effects of “school splits” along

socioeconomic lines on social integrationsocioeconomic lines on social integration Effect of random college/dorm assignment Effect of random college/dorm assignment

at Riceat Rice Field experiment – measure transmission Field experiment – measure transmission

of information through network by of information through network by disseminating job adsdisseminating job ads

THE ENDTHE END

Network FeaturesNetwork Features

ClusterednessClusteredness

Are the friends of your friends also your Are the friends of your friends also your friends?friends?

: , ,

: , ,

ij jk iki j i k j i

iij jk

i j i k j i

g g g

Clustercoefficientg g

Predictors of friendship:Predictors of friendship: High-school / AgeHigh-school / Age

OnlyOnlyHigh School, AgeHigh School, Age All CovariatesAll Covariates

Coef.Coef. Coef.Coef.

ConstantConstant 0.00390.0039 0.00280.0028

Same High SchoolSame High School 0.18640.1864 0.18590.1859

Same GenderSame Gender 0.00060.0006 0.00000.0000

Same Year in CollegeSame Year in College 0.00100.0010 0.00100.0010

Difference b/t Yrs in CollegeDifference b/t Yrs in College -0.0013-0.0013 -0.0011-0.0011

R2= 0.0293

Predictors of friendship: Predictors of friendship: BackgroundBackground

Only Only Family Family

BackgroundBackground All CovariatesAll Covariates

CoefCoef CoefCoef

ConstantConstant 0.00270.0027 0.00280.0028

Both from High Income HouseholdsBoth from High Income Households 0.00060.0006 0.00020.0002

Both from Low Income HouseholdsBoth from Low Income Households 0.00020.0002 0.00020.0002

2 College Parents - 2 College Parents2 College Parents - 2 College Parents 0.00140.0014 0.00090.0009

2 College Parents - 1 College Parent2 College Parents - 1 College Parent 0.00050.0005 0.00030.0003

2 College Parents - 0 College Parents2 College Parents - 0 College Parents1 College Parent - 1 College Parent1 College Parent - 1 College Parent

0.00000.00000.00030.0003

0.00000.00000.00020.0002

1 College Parent - 0 College Parents1 College Parent - 0 College Parents -0.0001-0.0001 -0.0001-0.0001

R2= 0.0001

Calibration Calibration Environmental Environmental

ParameterParameter ValueValue

# met initially, c# met initially, cinitinit 6.156.15

# met same college, c# met same college, ccollcoll 4.604.60

Probability same year, pProbability same year, pYEARYEAR .02.02

Probability same dorm pProbability same dorm pDORMDORM 0.350.35

cycles of friends of friendscycles of friends of friends 88

Probability meeting friend Probability meeting friend of friend (pof friend (pfrofrfrofr)) 0.540.54

Taste ParameterTaste Parameter ValueValue

ConstantConstant -1.72-1.72

Both WhiteBoth White 0.070.07

Both BlackBoth Black 2.102.10

Both HispanicBoth Hispanic 0.400.40

Both AsianBoth Asian 0.850.85

HiSATHiSAT 0.100.10

Parents EduParents Edu 0.090.09

ConservativeConservative 0.120.12

0

BB

HH

AA

WW

skillP arE du

C onserv

Segmentation by race vs. Segmentation by race vs. absolute and relative minority populationabsolute and relative minority population

y = -7.6794x + 4.1134

R2 = 0.0333

0

1

2

3

4

5

6

7

8

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

Fraction Asian

P A

sian

& A

sian

/ P

an

y tw

o y = -64.315x + 10.71

R2 = 0.2566

0

2

4

6

8

10

12

14

16

18

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

Fraction black

P B

lack

& B

lack

/ P

an

y tw

o

y = 0.0009x + 3.6018

R2 = 0.0231

0

1

2

3

4

5

6

7

8

0 200 400 600 800 1000 1200

Number of Asians

P A

sian

& A

sian

/ P

an

y tw

o

y = 0.0232x + 4.777

R2 = 0.1455

0

2

4

6

8

10

12

14

16

18

0 50 100 150 200 250 300

Number Black

P B

lack

& B

lack

/ /

P a

ny

two

Network FeaturesNetwork Features

0.0

05.0

1.0

15.0

2.0

25D

ensi

ty

0 50 100 150 200Number of friends

the old boy (and girl) network: social network formation on university campuses

Documents

social network formation

formation of social

role of social networks

social interaction

simulated network

girl network

friends of friends

substantial segmentation