+ All Categories
Home > Documents > Social Networks

Social Networks

Date post: 21-Mar-2016
Category:
Upload: artan
View: 33 times
Download: 0 times
Share this document with a friend
Description:
Social Networks. Obesity as a networked concept. The same goes for smoking …. www.tue-tm.org/INAM. All course info, literature, slides, and messages can be found here. Check regularly!. Today. Course design and content Introduction to network analysis and concepts. Lecturers. - PowerPoint PPT Presentation
Popular Tags:
64
TU/e - 0ZM05/0EM15/0A150 Social Networks 1
Transcript
Page 1: Social Networks

TU/e - 0ZM05/0EM15/0A150

Social Networks

1

Page 2: Social Networks

TU/e - 0ZM05/0EM15/0A150 2

Obesity as a networked concept

Page 3: Social Networks

TU/e - 0ZM05/0EM15/0A150 3

Page 4: Social Networks

TU/e - 0ZM05/0EM15/0A150

The same goes for smoking …

4

Page 5: Social Networks

TU/e - 0ZM05/0EM15/0A150 5

www.tue-tm.org/INAM

All course info, literature, slides, and messages can be found here.Check regularly!

Page 6: Social Networks

TU/e - 0ZM05/0EM15/0A150 6

Today Course design and content

Introduction to network analysis and concepts

Page 7: Social Networks

TU/e - 0ZM05/0EM15/0A150 7

Lecturers

Chris Snijders [email protected]

Uwe Matzat [email protected]

Rudi Bekkers [email protected]

Mila Davids [email protected]

Gerrit Rooks [email protected]

Page 8: Social Networks

TU/e - 0ZM05/0EM15/0A150 8

The course: organization

Three courses: 0ZM05(5 ects)0EM15 (6 ects)0A150 (3 ects)

Lectures every week on Wednesdays, hours 7 and 8. Later in the program less lecture time, more "assignment time" (see the course website).

Different courses, so not everybody has to do the same ...

Page 9: Social Networks

TU/e - 0ZM05/0EM15/0A150

Rough outline for the different courses(see online for the details)

9

Topic 0em15 0zm05 0a150

Basic stuff (about 5 lectures) Yes Yes Yes (have to be there)

Assignment CS Yes Yes YesAssignment UM Yes Yes NoPersonal and business networks + assignment GR

No No Yes

Dynamic capabilities and knowledge transfer in networks

Yes No No

Exam Yes Yes No

+ survey completion (so that you experience what a network survey feels like, and we can analyze the data during class and assignments)

Page 10: Social Networks

TU/e - 0ZM05/0EM15/0A150 10

Page 11: Social Networks

TU/e - 0ZM05/0EM15/0A150 11

Course requirements 0em15/0zm05:

Two (group of 2) assignments + written exam.

Grade = 50% assignments + 50% exam.

Both 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

Page 12: Social Networks

TU/e - 0ZM05/0EM15/0A150 12

To do: register in Studyweb(if possible)

Page 13: Social Networks

TU/e - 0ZM05/0EM15/0A150 13

Page 14: Social Networks

TU/e - 0ZM05/0EM15/0A150 14

Course aim

knowledge about concepts in network theory, and being able to apply that knowledge

(with an emphasis on innovation and alliances)

Page 15: Social Networks

TU/e - 0ZM05/0EM15/0A150 15

The setup in some more detail

Network theory and background

- Introduction: what are they, why important …- Four basic network arguments- Kinds of network data (collection)- Typical network concepts- Visualization and analysis

Page 16: Social Networks

TU/e - 0ZM05/0EM15/0A150 16

Some historical background and a general intro

Page 17: Social Networks

TU/e - 0ZM05/0EM15/0A150 17

"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. MorenoNew York Times, April 13, 1933

It’s about making our 'social space' visible

Page 18: Social Networks

TU/e - 0ZM05/0EM15/0A150 18

“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

We live in a connected world

Page 19: Social Networks

TU/e - 0ZM05/0EM15/0A150 19

Why do networks matter?

Page 20: Social Networks

TU/e - 0ZM05/0EM15/0A150 20

Why do networks matter?

Page 21: Social Networks

TU/e - 0ZM05/0EM15/0A150 21

Social Networks – a (cheesy) introduction

http://www.youtube.com/watch?v=6a_KF7TYKVc

Page 22: Social Networks

TU/e - 0ZM05/0EM15/0A150 22

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

Page 23: Social Networks

TU/e - 0ZM05/0EM15/0A150 23

The network perspective

A B

This depends on:•Cost effectiveness•Organizational structure•Corporate culture•Flexibility•Supply chain management•…

Two firms in the same market.Which firm performs better (say, is more innovative): A or B?

Page 24: Social Networks

TU/e - 0ZM05/0EM15/0A150 24

Two firms in the same market.Which firm performs better (say, is more innovative): A or B?

and ... on the structure of the network

A B

NoteNetworks are one way of dealing with “market imperfection”

The network perspective

Page 25: Social Networks

TU/e - 0ZM05/0EM15/0A150 25

Multi-level and interdisciplinaryNetwork applications appear in diverse substantive fields of mostly social sciences – anthropology, management, political science, public health, sociology (and recently also in economics)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

Page 26: Social Networks

TU/e - 0ZM05/0EM15/0A150 26

It's a science ...

Page 27: Social Networks

TU/e - 0ZM05/0EM15/0A150 27

Example: crime research

Example topics

-"Cold case" research- forensic psychiatry-(youth) crime-...

Page 28: Social Networks

04/24/23

Articles w ith Network* K eyword

SOURCES: Sociological Abstracts, EconLit

Y EAR

2000-041995-991990-941985-891980-841975-801970-751965-70

TOTA

L N

UM

BER

5000

4000

3000

2000

1000

0

SocAbs

EconLit

Page 29: Social Networks

TU/e - 0ZM05/0EM15/0A150 29

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).

Page 30: Social Networks

TU/e - 0ZM05/0EM15/0A150 30

Moreno’s socio-matrix

Page 31: Social Networks

TU/e - 0ZM05/0EM15/0A150 31

… displayed as a sociogram

Page 32: Social Networks

TU/e - 0ZM05/0EM15/0A150 32

Example: A targeted approach to HIV prevention

Think about similar examples for:

• Introduction of new products into target groups

• …

Page 33: Social Networks

TU/e - 0ZM05/0EM15/0A150 33

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)

Page 34: Social Networks

TU/e - 0ZM05/0EM15/0A150 34

Social network software

1) UCINet – Many things on network analysisLin Freeman, Steve Borgatti, Martin Everett

2) MultiNet – Whole Network Analysis + Nodal Characteristics

3) P*Star – Dyadic Analysis – Stan Wasserman

4) NodeXL (an Excel plugin) – Marc Smith

5) Pajek – Network Visualization – Supersedes Krackplot

6) StocNet – Tom Snijders - collected programs for, e.g., analysis of dynamic networks

7) … and many othersNB Even though computers are fast, really large networks can still be a real problem

Page 35: Social Networks

TU/e - 0ZM05/0EM15/0A150 35

Definitions and other boring stuff

Page 36: Social Networks

TU/e - 0ZM05/0EM15/0A150 36

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 2For instance:Actors: personsRelationships: “participates in the same course as”

Or:Actors: organizationsRelationships: have formed an alliance

Page 37: Social Networks

TU/e - 0ZM05/0EM15/0A150 37

Social network concepts: ties

Relationships can be directed:

Symmetrical by choice:

Symmetrical by definition:

(usually depicted as)

1 2For instance: person 1 likes person 2

Person 1 likes 2, 2 likes 1

1 2

1 2

1 2Person 1 is married to 2

Page 38: Social Networks

TU/e - 0ZM05/0EM15/0A150 38

Social network concepts: weights

Relationships can carry weights :

Actors can have a variety of properties associated with them:

1 2

Actors: personsRelationships: know each other 3 and 4 know each other better (stronger tie)

3 4

Page 39: Social Networks

TU/e - 0ZM05/0EM15/0A150 39

Social networks: translating arguments

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 32

Page 40: Social Networks

TU/e - 0ZM05/0EM15/0A150 40

Quantifying matters through network concepts

Actor characteristics: outdegree indegree betweenness ... (and many more)

Network characteristics density segmentation distribution of outdegrees ... (and many more)

Page 41: Social Networks

TU/e - 0ZM05/0EM15/0A150 41

More examples

Page 42: Social Networks

TU/e - 0ZM05/0EM15/0A150 42

An example of a modern network:9-11 Hijackers Network

SOURCE: Valdis Krebs http://www.orgnet.com/

Page 43: Social Networks

TU/e - 0ZM05/0EM15/0A150 43

OECD Trade Flows 1981-1992

SOURCE: Lothar Krempel http://www.mpi-fg-koeln.mpg.de/~lk/netvis.html

Note: practical use of visualization diminishes as networks grow larger

Page 44: Social Networks

TU/e - 0ZM05/0EM15/0A150 44

Internet facilitates social networking…

Page 45: Social Networks

TU/e - 0ZM05/0EM15/0A150 45

… for recreational use …

Page 46: Social Networks

TU/e - 0ZM05/0EM15/0A150 46

… also for business purposes …

http://www.youtube.com/watch?v=6SSR2tg5n_U

Page 47: Social Networks

TU/e - 0ZM05/0EM15/0A150

… or, if you want to create your own FaceBook-like site …

47

http://www.vivalogo.com/vl-resources/open-source-social-networking-software.htm

BTW Lots of businesses are willing to do the dirty work for you …

Page 48: Social Networks

TU/e - 0ZM05/0EM15/0A150 48

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>

Page 49: Social Networks

TU/e - 0ZM05/0EM15/0A150 49

… but the graph of actual connections is really different

Page 50: Social Networks

TU/e - 0ZM05/0EM15/0A150 50

… and can be restructured to reveal the “real” hierarchy!

Page 51: Social Networks

TU/e - 0ZM05/0EM15/0A150 51

Networks and innovation

Page 52: Social Networks

TU/e - 0ZM05/0EM15/0A150 52

Why networks & innovation?

Classic innovation studies focus mainly on characteristics of individuals or firms to explain innovation e.g. firm size and innovativeness

However, innovation, is inherently social in nature e.g. firms have relations with other firms and

consequently access to additional external resources

Hence, networks of social relations between actors (individuals and organizations) may be important factors

in explaining innovation and innovation may change networks of social relations

as well

Page 53: Social Networks

TU/e - 0ZM05/0EM15/0A150 53

CEO

Staff

Divisions

Master

Pupil

Guild

Second Industrial Revolution

Third Industrial Revolution

Master

Pupil

Master

Pupil

‘Stand alone’ model:- Economies of scale- Optimize assets

Networked model:Economies of skill: -access to knowledge-co-development-leverage knowledge-focus on core competences-learn and innovate

Why networks and alliance management?The knowledge economy is a network

economy

Organizational models are transforming from “stand alone” to “networked”

Page 54: Social Networks

TU/e - 0ZM05/0EM15/0A150 54

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

CEOs rate alliances among the most important management tools

Page 55: Social Networks

TU/e - 0ZM05/0EM15/0A150 55

Alliances lead to networks Network in Flat Screens 2000-2001

In 2 years time 75% of the firms in the industry are directly or indirectly connected

Source: De Man, 2006, Alliantiebesturing

Page 56: Social Networks

TU/e - 0ZM05/0EM15/0A150 57

Network questions and arguments

Page 57: Social Networks

TU/e - 0ZM05/0EM15/0A150 58

Typicalities of network arguments Non-linear effects can occur easily (cf “Small-world

phenomenon”) in networks [lecture 3]

Data collection often daunting

= “is being eaten by”

Page 58: Social Networks

TU/e - 0ZM05/0EM15/0A150 59

Page 59: Social Networks

TU/e - 0ZM05/0EM15/0A150 60

Typical network related questions 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

Page 60: Social Networks

TU/e - 0ZM05/0EM15/0A150 61

Networks = Y or Networks = XIn 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”)

Page 61: Social Networks

TU/e - 0ZM05/0EM15/0A150 62

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?

Page 62: Social Networks

TU/e - 0ZM05/0EM15/0A150 63

Using network arguments...

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”

Page 63: Social Networks

TU/e - 0ZM05/0EM15/0A150 64

Kinds of network arguments (in detail next week) 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

Page 64: Social Networks

TU/e - 0ZM05/0EM15/0A150 65

To Do: follow the directions on

www.tue-tm.org/INAM

Studyweb: register!


Recommended