Transcript Social Networks TU/e - 0ZM05/0EM15/0A150 Today  Course design and content  Introduction to network analysis and concepts TU/e - 0ZM05/0EM15/0A150

Social Networks
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Today
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Course design and content
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Introduction to network analysis and concepts
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Obesity as a
networked concept
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Who you are connected to
co-determines whether you
will become fat.
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The same goes for smoking …
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... and happiness
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Results are hot …
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(http://bit.ly/1uttKmH)
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Results are debated heavily ...
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Administration
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www.tue-tm.org/INAM

All course info,
literature, slides,
and messages can
be found here.
Check regularly!
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Lecturers
Chris Snijders
[email protected]
Uwe Matzat
[email protected]
Rudi Bekkers
[email protected]
Gerrit Rooks
[email protected]
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The course: organization
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Three courses:
0ZM05
(5 ects)
0EM15
(6 ects)
0A150
(3 ects)
Lectures every week on Wednesdays, hours 1 and 2,
AUD11. Later in the program less lecture time, more
"assignment time" (see the course website).
Different courses, so not everybody has to do the same ...
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Outline for the different courses
Topic
0em15
0zm05
0a150
Basic stuff (about 5 lectures)
Yes
Yes
Yes
Assignment 1
Yes
Yes
Yes
Assignment 2
Yes
Yes
No
Workshop personal networks
+ Assignment
No
No
Yes
Bekkers’ lectures
Yes
Yes
No
Assignment 3 (Bekkers)
Yes
No
No
Exam
Yes
Yes
No
(have to be
there)
+ survey completion (so that you experience what a network survey
feels like, and we can analyze the data during class and assignments)
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Course requirements
0em15/0zm05:
Assignments (0em15 has 3, 0zm05 has 2) +
written exam.
Grade = 50% assignments + 50% exam.
All assignments and the exam should be at least a
4.0. Final grade should be at least 5.5.
For 0a150 it’s the average of the two
assignments, where both should be at least 4.0
and the average at least 5.5. Attendance at the
first 5 lectures is mandatory for 0a150.
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To do: register for the course
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Course aim
gaining knowledge about concepts in
network theory, and being able to
apply that knowledge in different
contexts (which includes dealing with
network data)
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The setup in some more detail
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Introduction: what are they, why important …
Four basic network arguments
Network properties
Kinds of network data (collection)
(Calculation of) typical network concepts
Visualization and analysis
Small world networks
Applications in business networks
Patent networks
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Some historical background
and a general intro
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We live in a connected world
“To speak of social life is to speak of the
association between people – their
associating in work and in play, in love and
in war, to trade or to worship, to help or to
hinder. It is in the social relations men
establish that their interests find
expression and their desires become
realized.”
Peter M. Blau
Exchange and Power in Social
Life, 1964
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Social Networks –
a (cheesy) introduction
http://www.youtube.com/w
atch?v=6a_KF7TYKVc
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It’s about making our 'social space' visible
"If we ever get to the point of charting a
whole city or a whole nation, we would have
… a picture of a vast solar system of
intangible structures, powerfully influencing
conduct, as gravitation does in space.
Such an invisible structure underlies society
and has its influence in determining the
conduct of society as a whole."
Jacob L. Moreno
New York Times, April 13, 1933
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Yes we can!
A time of network data and possibilities
http://poptech.org/popcasts/quick_takes_sinan_aral
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Why do networks matter?
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Because you miss quite a bit of info...
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- Online social network (Facebook etc)
- Online data not based on being a social network (Ebay,
couchsurfing.com, firm board data etc)
- Phone logs / server logs / logs of energy use / other logs
...
- ...
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Social network analysis – it's core
An interdisciplinary perspective emphasizing structural
relationships as key explanatory concepts and principles:
• Structural properties of social formations are contexts
that shape the perceptions, beliefs, attitudes, and
actions of individuals and collectivities
• Social influence and collective action may be facilitated
and/or constrained by direct and indirect exchanges
(transactions) among social actors possessing
differential resources (e.g., information)
• Actors and transactions/interactions between actors
are embedded, i.e. located within actual situational
contexts
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The network perspective
Two firms in the same market.
Which firm performs better (say, is more innovative): A or B?
A
B
This depends on:
•Cost effectiveness
•Organizational structure
•Corporate culture
•Flexibility
•Logistics maturity
•…
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The network perspective
Two firms in the same market.
Which firm performs better (say, is more innovative): A or B?
A
B
Note
and ... on the structure of the network
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Networks are
one way of
dealing with
“market
imperfection”
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It's a science ...
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Multi-level and interdisciplinary
Network applications appear in diverse substantive fields of
social and natural sciences – anthropology, management,
political science, public health, sociology (and recently also in
economics), physics, computer science, complexity research
Studies span micro- meso- & macro-levels of analysis:
• personal social & health support systems
• children’s play groups, high school cliques
• employee performance
• neighboring behavior, community participation
• work teams, voluntary associations, social movements
• military combat platoons, terrorist cells
• corporate strategic alliances, board interlocks
• international relations: trade, aid, war & peace
•Internet relations: Twitter, LinkedIn, Facebook
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Example: crime research
Example topics
-"Cold case" research
- forensic psychiatry
-(youth) crime
-...
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And people are actually doing (things like) this more and
more …
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Articles with Network* Keyword
5000
4000
3000
SocAbs
2000
EconLit
1000
0
1965-70
1970-75
1975-80
1980-84
1985-89
YEAR
11/7/2015
SOURCES: Sociological Abstracts, EconLit
1990-94
1995-99
2000-04
Small-scale networks
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Network analysis: origins
Started in 1920s, Jacob L. Moreno
pioneered social network analysis for his
“psychodrama” therapy. He used
sociomatrices and hand-drawn sociograms
to display children’s likes and dislikes of
classmates as directed graphs (digraphs).
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Moreno’s socio-matrix
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… displayed as a sociogram
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Organizations as networks:
org-chart shows formal ties…
SOURCE: Brandes, Raab and Wagner (2001)
<http://www.inf.uni-konstanz.de/~brandes/publications/brw-envsd-01.pdf>
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… but the graph of actual connections
is really different
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… and can be restructured to reveal the “real”
hierarchy!
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Example: A targeted approach to HIV prevention
Think about similar examples for:
• Introduction of new products into target groups
(see next slide)
•…
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http://www.youtube.com/watch?v=xBIVlM435Zg
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Modern computing makes a big difference
“Visualization has been a key
component of social network
analyses from the beginning,
proliferating into today’s
dazzling computer-based
multidimensional displays”
(Freeman 2001)
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Social network software
1)
UCINet – Many things on network analysis
Lin Freeman, Steve Borgatti, Martin Everett
2)
Gephi
3)
P*Star – Dyadic Analysis – Stan Wasserman
4)
NodeXL (an Excel plugin) – Marc Smith
5)
Pajek – Network Visualization and calculation on larger networks
6)
7)
– mainly for visualization
StocNet – Tom Snijders - collected programs for, e.g., analysis of
dynamic networks
… and many others
NB Even though computers
are fast, really large networks
can still be a real problem
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Some definitions and network lingo
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Social network basics

A network (or graph)
contains a set of actors (or
nodes, objects, vertices),
and a mapping of relations
(or ties, or edges,
connections) between the
actors
1
2
For instance:
Actors: persons
Relationships: “participates in the same
course as”
Or:
Actors: organizations
Relationships: have formed an alliance
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Social network concepts: ties
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Relationships can be
directed:
1
2
For instance: person 1 likes person 2
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Symmetrical by choice:
1
2
Person 1 likes 2, 2 likes 1
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Symmetrical by definition: 1
2
Person 1 is married to 2
(usually depicted as)
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2
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Social network concepts: weights
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Relationships can carry
weights :
1
2
3
4
Actors: persons
Relationships: know each other
3 and 4 know each other better (stronger
tie)
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Actors can have a variety
of properties associated
with them:
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
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Social networks:
creating measures for “vague” concepts
There is reciprocity: whenever there is a tie from a to
b, there also is a tie from b back to a
Actor A is powerful: many connections go through A
1
2
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Quantifying matters through network concepts
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Actor characteristics:
 outdegree
 indegree
 betweenness
 ... (and many more)
Network characteristics
 density
 segmentation
 distribution of outdegrees
 ... (and many more)
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More examples
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An example of a modern network:
9-11 Hijackers Network
SOURCE: Valdis Krebs
http://www.orgnet.com/
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OECD Trade Flows 1981-1992
Note: practical
use of
visualization
diminishes as
networks
grow larger
SOURCE: Lothar Krempel
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http://www.mpi-fg-koeln.mpg.de/~lk/netvis.html
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Internet facilitates social networking…
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… for recreational use …
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… also for business purposes …
http://www.youtube.com/watch?v=6SSR2tg5n_U
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… or, if you want to create your own
FaceBook-like site …
http://www.vivalogo.com/vl-resources/opensource-social-networking-software.htm
BTW Lots of
businesses are willing
to do the dirty work for
you …
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Networks and innovation
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Why networks and alliances?
The knowledge economy is a network economy
Third Industrial Revolution
Second Industrial Revolution
CEO
Staff
Divisions
Guild
Master
Pupil
Master
Pupil
Master
Pupil
Networked model:
Economies of skill:
-access to knowledge
-co-development
-leverage knowledge
-focus on core
competences
-learn and innovate
‘Stand alone’ model:
- Economies of scale
- Optimize assets
Organizational models are transforming from “stand alone” to “networked”
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CEOs rate alliances among
the most important management tools
Bain researched the 25 most
popular management tools
in a survey among 960
international executives
• Alliances are among the 10 most
widely used tools by top
executives
• 63% of them use alliances
• Note that other tools involve
alliance and network related
aspects as well: CRM, outsourcing,
growth strategies, supply chain
management
Source: Rigby, 2005, Management Tools 2005, Bain & Company
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Alliances lead to networks
Network in Flat Screens 2000-2001
Source: De Man, 2006,
Alliantiebesturing
In 2 years time 75% of the firms in the industry are directly or indirectly connected
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Characteristic
network questions and
network arguments
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Different reasons for behavior: cascades
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Typicalities of network arguments
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Non-linear effects can occur easily (cf “Smallworld phenomenon”) in networks [lecture 4 or so]
Data collection often daunting when done on a
one-by-one basis
= “is being eaten by”
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Typical network related questions
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Which of these actors has the best position in the
network?
 Example: firms in alliance networks
Which kinds of networks are best for <…>
purposes?
 Example: R&D teams
Which are the key relations in the network?
 Example: terrorism
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Networks = Y
or
Networks = X
In most social science applications, networks are considered
as an independent variable.
For instance
Firm A performs better than B because firm A is embedded
in a network with a lot of ties (a network of higher “density”)
or
Person A performs better than B because person A has a lot
of ties to other persons and person B doesn’t
(firm A has a higher “outdegree”)
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Networks = Y
or
Networks = X
Sometimes: networks as the dependent variable
For instance:
How do the social networks of successful people differ from
the social networks of others? (and why is that?)
And, even rarer: dynamic network theory
For instance:
How do the friendship networks of people change over time?
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Using network arguments...
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Make sure that you define the actors/nodes, and
what the ties between them represent (directed?,
weighted?).
Make clear how and what (kind of) network
characteristics drive your result. There are so
many network characteristics … think hard!
Shop around for arguments in areas unrelated to
your own! (where perhaps only the nodes and the
ties are different!)
“The best ideas already exist”
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Kinds of network arguments
(in detail later in the course)
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Closure competitive advantage stems from managing risk; closed
networks enhance communication and enforcement of sanctions
Brokerage competitive advantage stems from managing
information access and control; networks that span structural holes
provide the better opportunities
Contagion information is not a clear guide to behavior, so
observable behavior of others is taken as a signal of proper
behavior.
[1] contagion by cohesion: you imitate the behavior of those
you are connected to
[2] contagion by equivalence: you imitate the behavior of those
others who are in a structurally equivalent position
Prominence information is not a clear guide to behavior, so the
prominence of an individual or group is taken as a signal of quality
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To Do:

follow the directions on
www.tue-tm.org/INAM

In particular:
read chapters 1-3 of the book by Hanneman
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