Dynamics of Social Interaction Frequency: Role of Geography and Accessibility

Fariya Sharmeen

Background

• People are space bound.

• Social networks also are embedded in a spatial setting.

• Studies on social networks recognize distance in • Studies on social networks recognize distance in geographical space as a determinant of distance in network links in terms of tie strength between an ego and alters.

• Thus geography matters for social interactions as much as anything else

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Background

Which geographical features?

• Distance to alters

• Accessibility to Transport infrastructures

• Accessibility to Facilities

• Degree of Urbanization

History of interaction

Dynamics of distance

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Background

Why this is important?

1. Acknowledge the role of geographical features in explaining social interaction

2. Comprehensive modelling approach2. Comprehensive modelling approach

3. can provide useful direction to sustainable community design and can strengthen social cohesion policies.

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Theory and Concepts

a

c

c

e

s

s

i

b

h

o

m

o

p

Social Interaction

Accessibility to

facilities and

transport

infrastructures

Ego-Alter tie

characteristics

Degree of

urbanization

Ego’s socio

demographics

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path dependency life course approach

b

il

it

y

p

h

il

y Geographical

distance with alter History of social

interaction

Changes in

geographical

distance with alter

Research Questions

• To what extent are social interaction/activity frequencies path dependent?

• Does a change in geographical distance with alters influence social interaction/activity frequency?

• What are the effects of urbanization and accessibility to social/recreational facilities on social interaction/activity frequency?

• What are the effects of life cycle-events on social interaction/activity frequency?

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Data

Event based retrospective survey

1.Socio demographics

2.Present social network

3.Dynamics in social network

4.Dynamics in Activity Travel schedule4.Dynamics in Activity Travel schedule

Netherlands

700 respondents

September 2011

8458 ties

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Data

Cetral Bureau of Statistics, Netherlands

Degree of urbanization and

Accessibility to facilities

within neighbourhood – defined by 4 digit postcode

20062006

Open street map

calculate distance to city/town/village center

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Methodology

Ordered Logit model

Extension 1: Random effects model

1 1

1

n

ijt itk itk ij

k

y xβ ε=

= +∑

n n n

y x x xβ β β α ε= + + + +∑ ∑ ∑

Extension 2: Path dependence model

1 1 2 2 3 3

1 1 1

n n n

ijt itk itk ijtk ijtk itk itk i ij

k k k

y x x xβ β β α ε= = =

= + + + +∑ ∑ ∑

ijitij

n

k

ktijktij

n

k

itkitk

n

k

ijtkijtk

n

k

itkitkijt yxxxxy εαββββ ++++++= −

=

−−

===

∑∑∑∑ )1(

1

)(2)1(2

1

33

1

22

1

11

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Descriptives

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Results

Model 1:Basic

Model 2: Random

Model 3: Random effects with land use

Model 4: Random effects with

Model 5:Random effects with

Ordered logit model of face-to-face interaction frequency

Dependent variable face o face interaction frequency

(0=none, 1=less, 2=once a month, 3=2-3 times a month, 4=once a week,

5=2-3 times a week, 6=daily)

Basic model

Random effects model

with land use and accessibility indicators

effects with state dependence

effects with interaction variables

Log likelihood function -14589.34 -14262.48 -14245.97 -12276.56 -12262.65

Restricted log likelihood

-15514.46 -14589.34 -14562.30 -12582.74 -12567.12

Chi square 1850.24*** 653.71*** 632.65*** 612.36*** 608.93***

# of Parameters 34 35 44 49 54

AIC/N 3.458 3.381 3.379 2.915 2.912

∆i=Exp(-∆AIC /2) 6.70 4.85 3.30 1.34 1

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Results

6 groups of variables

I1: Ego’s socio demographicsI2: Ego-alter tie characteristicsI3: Life cycle eventsI4: Density and Aceessibility indicatorsI5: History of social interactions and distanceI6: interaction effects

I1: Ego’s socio demographics β t

AGE21-30 0.352 *** 7

Gender: male -0.007 -0.25

No car 0.319 *** 7.91

Driving license: yes 0.144 *** 4.19

HH with children -0.081 ** -2.17

HH without children -0.151 *** -3.67

HH with friends -0.080 -1.6

Work hr per week 0.001 1.33

Size of Social network -0.103 *** -7.45

# club membership 0.082 *** 3.45

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Results

I2: Ego-alter tie characteristics β t

Same age group -0.119 *** -4.57

Same education level 0.218 *** 5.07

Same gender 0.169 *** 6.24

Age difference: upto 2 category 0.011 0.46

Education level difference: upto 2 category -0.028 -0.73

Relation: neighbour 0.203 *** 4.69Relation: neighbour 0.203 *** 4.69

Relation: friend 0.239 *** 8.2

Relation: family 0.272 *** 7.49

Relationship strength: weak -0.893 *** -19.13

Relationship strength: medium -0.315 *** -12.46

Distance: 0-1 km 2.739 *** 46.67

Distance: 2-5 km 0.284 *** 7.21

Distance: 6-30 km 0.257 *** 6.98

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Results

I3: Life cycle events β t

Event: change in work/study 0.056 0.81

Event: children start school 0.092 1.12

Event: change in residence -0.108 *** -2.71

Event time: 6-12 months -0.161 *** -4.6

Event time: 0-6 months -0.202 *** -6.1

I4: Density and accessibility indicators β t

Distance to city centre (log) -0.011 * 1.68Distance to city centre (log) -0.011 * 1.68

Rural area 0.064 * 1.92

Suburban area -0.057 * -1.86

#Shopping within 1 km 0.014 * 1.67

#Café/Restaurant within 1 km -0.002 *** -6.53

#Attractions within 10 km -0.015 *** -2.41

Distance to highway (log) 0.034 * 1.79

Distance to train station (log) -0.031 * -1.76

Distance to public green (log) 0.001 -0.62

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Results

I5: History of social interaction and distance β t

F2F before: daily 3.342 *** 89.85

F2F before: weekly 2.200 *** 60.84

F2F before: monthly 0.812 *** 17.39

NOWFAR -0.425 ** -2.13

NOWCLOSE -0.059 -1.01

I6: Interaction effects β t

Neighbour*change in residence -0.347 *** -5.07

NOWFAR*change in residence 0.412 *** 2.35NOWFAR*change in residence 0.412 *** 2.35

NOWFAR*change in work/study 0.104 0.56

NOWCLOSE*change in work/study -0.144 *** -3.48

NOWCLOSE*change in residence 0.251 *** 5.27

β t

Mu(01) 1.632 66.96

Mu(02) 2.483 96.24

Mu(03) 3.116 114.0

Mu(04) 3.938 142.4

Mu(05) 5.003 163.2

β t

Sigma 0.482 20.82

Threshold parameter

Std Deviation random effect

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Answers to Research Questions

• Face-to-face social interaction frequencies are strongly path dependent.

• Findings support that change in geographical distance affect social interaction frequency.

• Varied effects of degree of urbanization, accessibility to facilities and transport infrastructures were observed and reported.

• Social interaction/activity frequency dynamics are subject to the type of event.

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Conclusion

• The study aims to model face to face social interaction frequency taking the effects of accessibility, degree of urbanization, and path dependency.

• It shows that inclusion of local geographical and accessibility indicators and long term dynamics accessibility indicators and long term dynamics improves model performance.

• The findings add to the long debated body of literature in sociology about distance decay in social relationships.

• The novel contribution is the inclusion of the effects of changes induced by life-cycle events.

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Next?

• In depth analysis of purpose and location-type choice

• Alter’s home location

• Preferences, limitations of individuals• Preferences, limitations of individuals

• Ethnic and migrated neighbourhoods

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Thank you

Fariya SharmeenFariya Sharmeen

f.sharmeen@tue.nl