2. Aims Lecture 9
To understand:
To study characteristics of networks
Networks as social capital
The problem of only a structuralist approach+
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+
Homophily
Reciprocity
Centrality
4. Some Questions
Social network research requires
general theories to answer:
Can the effects of networks (i.e., on behavior) be generalized
across situations?
In Network Research
a.
5. Some Questions
Social network research requires
general theories to answer:
Can the effects of networks (i.e., on behavior) be generalized
across situations?
In Network Research
a.
Why certain network effects sometimes occur and sometimes not?b.
and if not,
i.e., Why is there more clustering in some networks than in others?
8. Structuralism
Structure overrides preferences
A first approach
You can explain people’s actions by only
knowing the structure of their social network
Claims:
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+
Give me the network & I will tell
you what the actors will do
9. Selling Point
Labor markets (Granovetter, 1974)
Of this perspective
Illegal services: Abortion (Lee, 1969)
All markets:
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Are socially organized in networks
10. Selling Point
Labor markets (Granovetter, 1974)
Of this perspective
Illegal services: Abortion (Lee, 1969)
All markets:
+
+
Are socially organized in networks
Role equivalence:
Persons are tied not to the same persons but to similar persons
(Wasserman & Faust, 1994)
11. Selling Point
Labor markets (Granovetter, 1974)
Of this perspective
Illegal services: Abortion (Lee, 1969)
All markets:
+
+
Are socially organized in networks
Role equivalence:
Persons are tied not to the same persons but to similar persons
(Wasserman & Faust, 1994)
Two positions in the aggregate: an elite person
(well-connected) & a hanger-on (not well-connected)
13. Main Problems
Think about the micro-macro link
Of structuralism
It lacks a theory of individual behavior
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14. Main Problems
Think about the micro-macro link
Of structuralism
It lacks a theory of individual behavior
+
Rational Choice Perspective:
Conceives networks as social resources
15. Main Problems
Think about the micro-macro link
Of structuralism
It lacks a theory of individual behavior
+
Rational Choice Perspective:
Personal networks can be treated as social capital
that is instrumental in reaching our goals
Conceives networks as social resources
17. Not a new idea
Thomas Hobbes
English philosopher
1588-1679
To have friends is to have power:
for they are strengths united
Since Hobbe’s Leviathan:
18. Networks as Social Capital
Networks are treated as a
specific resource important for
most goals people have in life.
19. Networks as Social Capital
Two main propositions in S.C. Theory
Networks are treated as a
specific resource important for
most goals people have in life.
20. Networks as Social Capital
Two main propositions in S.C. Theory
Networks are treated as a
specific resource important for
most goals people have in life.
1 Social Resource Hypothesis: people better equipped with social
capital will be better able to attain their goals
21. Networks as Social Capital
Two main propositions in S.C. Theory
Networks are treated as a
specific resource important for
most goals people have in life.
1 Social Resource Hypothesis: people better equipped with social
capital will be better able to attain their goals
2 Investment Hypothesis: people will invest in social capital
according to its instrumental value in producing their ends
22. Networks as S.C.
It explains the emergence as well as the
effects of social networks
23. Networks as S.C.
It explains the emergence as well as the
effects of social networks
A person’s social capital promotes her goal achievement
24. Networks as S.C.
It explains the emergence as well as the
effects of social networks
She will invest in it depending on its instrumental value
&
A person’s social capital promotes her goal achievement
25. Networks as S.C.
It explains the emergence as well as the
effects of social networks
Macro-micro link
She will invest in it depending on its instrumental value
&
A person’s social capital promotes her goal achievement
26. Networks as S.C.
It explains the emergence as well as the
effects of social networks
Macro-micro link
She will invest in it depending on its instrumental value
Micro-macro link
&
A person’s social capital promotes her goal achievement
29. Homophily
If instead of just looking at the network
We keep track of characteristics of the nodes (i.e., attributes)
Lazarsfeld & Merton (1954)
30. Homophily
If instead of just looking at the network
We keep track of characteristics of the nodes (i.e., attributes)
We tend to find that link nodes are similar to each other
Lazarsfeld & Merton (1954)
31. Homophily
If instead of just looking at the network
We keep track of characteristics of the nodes (i.e., attributes)
We tend to find that link nodes are similar to each other
Birds of a feather flock (will fly) together
Philemon Holland, 1960
Lazarsfeld & Merton (1954)
33. Real-life networks
Homophily
Only 8% of people have any people of another race that
they discuss important matters with (Marsden, 1987)
Race & friendship networks US:
Interracial marriages US:
Gender & friendship networks
34. Real-life networks
Homophily
Only 8% of people have any people of another race that
they discuss important matters with (Marsden, 1987)
Race & friendship networks US:
1% of white marriages, 5% of black marriages, 14% of
asian marriages (Fryer, 2006)
Interracial marriages US:
Gender & friendship networks
35. Real-life networks
Homophily
Only 8% of people have any people of another race that
they discuss important matters with (Marsden, 1987)
Race & friendship networks US:
1% of white marriages, 5% of black marriages, 14% of
asian marriages (Fryer, 2006)
Interracial marriages US:
Closest friends: 10% of men name a woman, 32% of
women name a man (Verbrugge, 1977)
Gender & friendship networks
36. Real-life networks
Homophily
Only 8% of people have any people of another race that
they discuss important matters with (Marsden, 1987)
Race & friendship networks US:
1% of white marriages, 5% of black marriages, 14% of
asian marriages (Fryer, 2006)
Interracial marriages US:
Closest friends: 10% of men name a woman, 32% of
women name a man (Verbrugge, 1977)
Gender & friendship networks
In all cases lower than if ignoring attributes
38. Possible Explanations
Reasons for Homophily
The possibility that you meet people
could be biased by attributes (i.e, race)
Opportunity (Contact Theory):
Benefits/Costs:
More of a chance of meeting your own type
39. Possible Explanations
Reasons for Homophily
The possibility that you meet people
could be biased by attributes (i.e, race)
Opportunity (Contact Theory):
Benefits/Costs:
More of a chance of meeting your own type
Common attributes (i.e., language,
culture, knowledge) make it easier
40. Possible Explanations
Reasons for Homophily
The possibility that you meet people
could be biased by attributes (i.e, race)
Opportunity (Contact Theory):
Benefits/Costs:
Also social pressure or social competition
More of a chance of meeting your own type
Important:
Common attributes (i.e., language,
culture, knowledge) make it easier
41. Possible Explanations
Reasons for Homophily
The possibility that you meet people
could be biased by attributes (i.e, race)
Opportunity (Contact Theory):
Benefits/Costs:
Also social pressure or social competition
More of a chance of meeting your own type
Common attributes (i.e., language,
culture, knowledge) make it easier
Important:
The structure of the network depends on the characteristics
i.e., why communication might circulate among one group and not another?
43. Quick Summary
two points
From Structuralism:
The characteristics of the network matter. They affect the
individuals
From Homophily (Segregation Patterns):
44. Quick Summary
two points
From Structuralism:
The characteristics of the network matter. They affect the
individuals
From Homophily (Segregation Patterns):
The characteristics of the individuals matter. They affect the
structure of the network
50. Reciprocity
Local Patterns
Directed Networks
A node can be linked to another without the second being
linked to the first (i.e., webpages)
Reciprocity
There is a tendency to dyadic reciprocation in most directed
networks
ij in g does not imply ji in g
51. Reciprocity
Local Patterns
Directed Networks
A node can be linked to another without the second being
linked to the first (i.e., webpages)
Reciprocity
There is a tendency to dyadic reciprocation in most directed
networks
ij in g does not imply ji in g
if ij in g it is more likely ji in g
55. Reciprocity
Explanation
Mutual Dependence
Actors (i.e., players, people) depend on each other for valued
outcomes, and benefits will be received from another actor
only if they are also given in return
Think about
Cooperation: if relations are not reciprocated they are likely
to be terminated more rapidly
(Emerson, 1972)
56. Reciprocity
Explanation
Mutual Dependence
Actors (i.e., players, people) depend on each other for valued
outcomes, and benefits will be received from another actor
only if they are also given in return
Think about
Cooperation: if relations are not reciprocated they are likely
to be terminated more rapidly
(Emerson, 1972)
Keeping a non-reciprocated relation implies status deference
tend to be eliminated
59. Node Centrality
Positions in Networks
Who are influential, powerful
(Think of our Facebook Example with Ana)
How different nodes are positioned in the network?
60. Node Centrality
Positions in Networks
Who are influential, powerful
(Think of our Facebook Example with Ana)
How different nodes are positioned in the network?
Many social networks show a fair extent of centralization
61. Node Centrality
Positions in Networks
Who are influential, powerful
(Think of our Facebook Example with Ana)
How different nodes are positioned in the network?
Many social networks show a fair extent of centralization
differentiation between social actors with
respect to their centrality
64. Node Centrality
2
1 4
1 2
4
1 3
3 2
3 2
2
2
Both white nodes have degree 2 (degree centrality)
The first seems more central - neighbors (3) & (4): (betweenness)
Better connected in another sense
Example
Ways of measuring centrality
65. Node Centrality
2
1 4
1 2
4
1 3
3 2
3 2
2
2
There are many other measures of centrality
Both white nodes have degree 2 (degree centrality)
The first seems more central - neighbors (3) & (4): (betweeness)
Better connected in another sense
Example
Ways of measuring centrality
67. Node Centrality
Why do we observe it?
It reflects social organization and opportunities
A strongly centralized network increases the likelihood of collective
action in mobilizations - easier contact to others
(Marwell, Oliver & Prahl, 1988)
68. Node Centrality
Why do we observe it?
Result of feedback processes
Favoring the creation of links to nodes that are already highly connected
It reflects social organization and opportunities
A strongly centralized network increases the likelihood of collective
action in mobilizations - easier contact to others
(Marwell, Oliver & Prahl, 1988)
69. Node Centrality
Why do we observe it?
Result of feedback processes
Favoring the creation of links to nodes that are already highly connected
It reflects social organization and opportunities
A strongly centralized network increases the likelihood of collective
action in mobilizations - easier contact to others
(Marwell, Oliver & Prahl, 1988)
Unto him that hath is given and from him that
hath not is taken away, even that which he hath
The Matthew effect (Merton, 1968)
70. Node Centrality
Why do we observe it?
Result of feedback processes
Favoring the creation of links to nodes that are already highly connected
It reflects social organization and opportunities
A strongly centralized network increases the likelihood of collective
action in mobilizations - easier contact to others
(Marwell, Oliver & Prahl, 1988)
Unto him that hath is given and from him that
hath not is taken away, even that which he hath
The Matthew effect (Merton, 1968)
However, centralization is most likely in physical networks: Internet hubs
72. Both structure of the network & individual behavior (and
characteristics) influence each other
Checklist
73. Both structure of the network & individual behavior (and
characteristics) influence each other
Checklist
People use their social networks as a form of capital that
helps them achieve what they want
74. Checklist
People use their social networks as a form of capital that
helps them achieve what they want
Social networks portray different properties:
Both structure of the network & individual behavior (and
characteristics) influence each other
75. Checklist
People use their social networks as a form of capital that
helps them achieve what they want
Social networks portray different properties:
Individuals with common traits are likely to be related (Homophily)
Most relationships are reciprocal (both parts aim for it)
We can look locally at who is influential (centrality)
Important for diffusion of information
Both structure of the network & individual behavior (and
characteristics) influence each other
