Samenvatting
Summary Advanced Sociological Theory (MoSi) End-Term (ENG)
- Instelling
- Universiteit Utrecht (UU)
Summary from the literature from mid-term till end of the course.
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ADVANCED SOCIOLOGICAL THEORY:Modelling Social Interaction
Summary part II
Inhoud
Week 5..........................................................................................................................................................................................................2
5.1 Lecture – Segregation revisited......................................................................................................................................2
5.1.1 From micro to macro: agent based modelling and simulation......................................................2
5.1.2 Example: Schelling’s segregation model........................................................................................................3
5.1.3 Schelling’s model compared...................................................................................................................................4
5.1.4 Computer simulation as a theoretical tool in social science............................................................5
5.2 Literature.......................................................................................................................................................................................6
5.2.1 Schelling - Models of segregation (1969).........................................................................................................6
5.2.2 Schelling – Micro motives and macro behaviour (1978)......................................................................7
5.2.3 Gilbert & Troitzsch – Simulations for the Social Scientist...................................................................9
Week 6........................................................................................................................................................................................................13
6.1 Lecture – Social Interaction, Diffusion and Social Change.......................................................................13
6.1.1 The explanatory problem: dynamics of mass collective action.....................................................13
6.1.2 A basic model: Granovetter’s Threshold model.......................................................................................13
6.1.3 Extensions of the model: diffusion of social networks........................................................................17
6.2 Literature.....................................................................................................................................................................................17
6.2.1 Granovetter – Threshold models of Collective Behavior (1978).....................................................17
Week 7......................................................................................................................................................................................................20
7.1 Lecture – Social norms.......................................................................................................................................................20
7.1.1 What are norms and why study them?.........................................................................................................20
7.1.2 The ‘demand’ for and the realization of norms........................................................................................21
7.1.3 Special cases.....................................................................................................................................................................23
7.2 Literature.....................................................................................................................................................................................23
7.2.1 Voss – Game-Theoretical Perspectives on the emerge of Social Norms (2001)...............23
Week 8......................................................................................................................................................................................................26
8.1 Lecture – Relative deprivation & summary.........................................................................................................26
8.1.1 Social conditions and social unrest...................................................................................................................26
8.1.2 A broader perspective: relative deprivation...............................................................................................27
8.1.3 Boudon’s model of relative deprivation........................................................................................................27
8.2 Literature....................................................................................................................................................................................30
8.2.1 Boudon – The Logic of Social Action (1981).................................................................................................30
, 8.2.2 Hedström – Chapter 7................................................................................................................................................31
W eek 5
5.1 Lecture – Segregation revisited
5.1.1 From micro to macro: agent based modelling and simulation
In the second part of the course the focus will
be on macro. The emphasis is about
Model building in sociology
understanding how individual actions
aggregate and lead to certain collective
outcomes (the transformation rules of Model: Explanation with simplified
Coleman’s boat). assumptions
Individual actions → ? → Collective outcomes
Where and what to simplify?
A way to explain how individual actions lead 1. Assumptions about individuals as
to collective actions is agent-based MUCH as possible
modelling. 2. Assumptions about social conditions
Agent-based modelling is used to explain as LITTLE as possible
complex social phenomena. It is:
Goal: Derive implications regarding
1. Bottom-up approach
effects of social conditions on collective
You start with individual behaviour, and
effects
then you grow toward social
phenomena from these behaviours.
2. Agents follow simple behaviour rules Decreasing abstraction (Lindeberg):
Keep things simple, so the model will Stepwise replacement of simplification
be useful by more realistic assumptions, so your
3. Social interaction between agents model will become more useful and
realistic
The goal of agent-based modelling is to study
how social phenomena emerge from the
interaction of simple agents.
A few examples of agent-based models are
climate change models, models about how birds move, etc. They are simulations, mostly on
the computer.
Simulations aim to:
Help understand complex systems with many moving parts
Sometimes help predict like with weather or crowd models
In social science the ‘moving parts’ are actors
In social science used as an automated thought experiment:
1. Build a simplified model of a social process
2. Translate the model into computer code
3. Let the computer run the model
4. Make changes to the conditions to see what happens!
Derive hypotheses from the model.
,5.1.2 Example: Schelling’s segregation model
In the first lecture we talked about residential segregation (see figure below). We saw that
the common sense theory couldn’t be used to explain why there was residential
segregation. But what can explain it?
P1 T1 E1 P2
Problem Theory Emperical research New problem
Explanatory problems: Common- sense theory Refutation of common- 1. Why is residential
1. Trends sense theory segregation unaffected
2. Noth-South by changes/differences in
comparison the percentage of whites
approving integration?
2. Why are integrated
situations unstable?
Enter Schelling’s model!
For this model we need two things:
1. A town
2. People in the town with:
a. preferences where to live
b. options where to move
Let’s create the setting:
Unidimensional town:
o From left to right, 70 ‘households’ in a row
(other possibilities are also possible like a circle, or a grid)
Two races: Black (O) and white (#)
Your model should look like this now:
…O##OO#O#O#O#OO####O…
Then add some definitions and assumptions:
The neighbourhood consist of:
o Household itself
o Four households to the left
o Four households to the right
Households near the end of the line have fewer neighbours.
A neighbourhood should look like this now:
OO#O#OO#
Now where do they move to?
The game proceeds in rounds as segregation is a dynamic process
At the beginning of each round, identify unhappy households.
o Unhappy: More than half of the neighbourhood has the opposite colour.
o Preference of household: Avoid minority situation
o Social condition: composition of neighbourhoods
o Individual motives (avoiding a minority situation) lead to collective effects
(segregation)
, Order of moving: Unhappy pieces move in turn, counting from left to right
How households move: A piece moves to the nearest point between two other
households to the right or to the left where it is not a minority
o Moves are costly: costs increase in distance
o No scarcity on the housing market
o No legal or economic constraints to choosing certain neighbourhoods
o No discrimination on the housing market
If the neighbourhood of the marked household has changed such that not more than
half of the neighbours have the opposite colour when the turn to move comes, the
marked piece does not move at all
o Interdependence between households
End of a round: Each household that has been marked at the beginning of the round
has had a turn to move
End of the game: Each piece has a neighbourhood with at least half of the
neighbours of the same colour.
o Or there is no suitable place to move to.
5.1.3 Schelling’s model compared
DBO
If we look at Schelling model
through the DBO-lens, you
would get this:
His model is opportunity-
mediated, because the moving
of actor j influences the
opportunities (available houses)
for actor i, which results in
moving.
1
Note that a few rounds are missing, but this process gives a general idea of the model
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