Innovation in networks week 2

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Innovation in networks week 2

• Social capital, closure,
• and structural holes
• Chris Snijders
• c.c.p.snijders_at_tm.tue.nl

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Innovation? (something new)
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Innovation and social network theory

• How do innovations come into being? ? this weeks
  emphasis
• What happens with innovations?a) How and when do
  they spread (adoption)?b) How and when are they
  used?
• Which consequences do innovations have? (for
  individuals, markets, organizations, companies,
  society, )
• Claim
• Social Network Analysis (SNA) provides crucial
  insights for the answers
• to all three (groups of) questions!

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Any experience? (MGO2, STI3, )

• Theory
• social capital
• weak vs strong ties (Granovetter)
• structural holes (Burt)
• closure (Coleman)
• (small world networks / the Kevin Bacon effect)
• Techniques
• data collection through surveys
• network measures
• Ucinet or other programs used to grind network
  data
• SPSS or other general statistics programs to deal
  with data
• Application of the above to a specific (own) topic

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Before I forget

• As does most good science, we (want you to)
  work with the Problem-Theory-Observation cycle
• Define your research Problem formulation
• Think about a general answer to this problem a
  Theory
• Test you theory on the basis of Observation
• (which leads to new Problem formulations)
• First couple of weeks all theory.
• Note this does not imply that you should
  believe what other researchers have claimed is
  all true! It is all empirically testable though.

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Social networks dots with lines or arrows in
between

• Examples
• unit (dot) type of
  relationship
• (line or arrow)
• pupils of a school class
  friendship
• employees of a company communication,
  authority relation
• members of a local community membership in
  the same club
• companies
  business relationship

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Topics of today

• Classic readings in social network analysis
• Coleman Social capital in the creation of human
  capital
• Burt Structural holes versus network closure as
  social capital
• Granovetter The strength of weak ties
  (revisited)
• Keywords
• Social capital
• Closure
• Structural holes
• Weak ties, strong ties

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Coleman Social capital in the creation of human
capital

• Social capital vs human capital
• (or, as some say sociology vs economics)
• Empirical analysis
• To explain school dropouts
• Network actors pupils and their parents
• Network ties having frequent contact with

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Coleman Social capital in the creation of human
capital (2)

• SEVERAL DEFINITIONS OF SOCIAL CAPITAL
• OF A PERSON
• The resources you can mobilize through others
• The value of social networks that people can draw
  on to solve common problems. The benefits of
  social capital flow from the trust, reciprocity,
  information, and cooperation associated with
  social networks.
• OF A SOCIETY
• The attitude, spirit and willingness of people to
  engage in collective, civic activities the
  social infrastructure
• A "composite measure" which reflects both the
  breadth and depth of civic community (staying
  informed about community life and
• participating in its associations) as well as
  the public's
• participation in political life
• people tend to say that nowadays social capital
  is declining in Western societies
• The collective value of all social networks

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Coleman Social capital in the creation of human
capital (2)

• Human capital the competencies and resources
  you have available yourself (e.g., wealth,
  intelligence, education, experience, )
• Social capital the resources you can mobilize
  through others the way in which your
  connections to others facilitate achieving ones
  goals
• Note
• Human capital can be social. For instance
  having good social skills is an example of human
  capital.
• Social capital need not be social. For
  instance a firm in a network of business partners

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Coleman Social capital in the creation of human
capital (3)

• General background there were two classical
  streams of thought
• One should consider the behavior of rational
  individuals trying to optimize their utility (and
  utility money) ? economics
• Individuals are at the mercy of social conditions
• Two new streams emerge, creating a convergence
  between sociology and economics
• Effects of social conditions on economic action
• - For instance Baker (1983) about the Chicago
  Options Exchange
• Understanding social behavior as a consequence of
  rational action
• - For instance Becker (1991) on behavior in the
  family A treatise on the family
• Coleman is somewhere in between the latter two
  streams.
• His best known work Foundations of social theory
  (1990)
• Born 1926, died 1995
• 1966 Coleman Report. Large datasets on schools
  and racial segregation.
• The study suggested that busing might be a
  good idea.
• 1974 New data showed that busing lead to
  emigration of whites from
• their neighborhood, and Coleman
  changed his opinion.

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Coleman Social capital in the creation of human
capital (4)

• Two of Colemans social capital examples
• Raising kids in Jerusalem vs in Detroit
• The diamond merchants
• Compare
• Diego Gambettas 1996 The sicilian mafia
• (? social capital need not be good for society)
• Putnams Bowling alone Social capital is
  declining
• in the US (and according to him, this has
  something
• to do with privatization and television)

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Coleman Social capital in the creation of human
capital (5)

• Social capital (of a society or group) consists
  of
• Obligations and expectations
• El Khalili market in Cairo
• Private credit organizations (e.g., Chinese
  restaurants in NL)
• Channels of information
• Granovetter Strength of weak ties
• Norms about what (not) to do
• all kinds of collective action problems can then
  be solved
• (Dutch government Postbus 51)
• Dutch example code Tabaksblat, a commission on
  corporate governance restricting the use of huge
  bonuses in the business world
• For 1. and 3. you need closure (dense networks
  between actors / connections between your ties)
  or ensure it through social organization. Note
  that Coleman is less clear about the need of
  closure for 2.

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Coleman Social capital in the creation of human
capital (6)

• Social capital (of parents) can lead to human
  capital (of children)
• Empirical analysis
• To explain school dropouts
• Network actors pupils and their parents
• Network ties having frequent contact with
• To do well in school, you need
• Financial capital (physical resources)
• Human capital (cognitive environment)
• AND Social capital (access to human capital)
• Coleman argues that social capital really helps
  pupils. Pupils whose parents spend more time on
  them, tend to be in Catholic schools parents
  know each other from church related meetings, or
  have stayed in the same neighborhood parents
  know each other better, indeed drop out less
  often.
• Note social capital can be a collective good
  (or at least at odds with what one would
  generally want). Example stable neighborhoods.

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Ron BurtStructural holes versus network closure
as social capital

• Burts conclusion
• structural holes beat network closure
• when it comes to predicting which actor
• performs best
• Coleman says closure is good
• Because information goes around fast
• and it facilitates trust
• fear of a damaged reputation
• precludes opportunistic behavior
• He subsequently compares people with
• dense networks with those with
• networks rich in structural holes

University of Chicago graduate school of business
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Social organization (Fig 1 in the paper)
Structural holes create value
A
B
1
7
3
2
James
Robert
4
5
6

• Robert will do better than James, because of
• informational benefits
• tertius gaudens (entrepreneur)

C
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Structural holes / Redundancy

• It is not that clear (yet) what precisely
  constitutes a structural hole.
• But Burt does define two kinds of redundancy in a
  network
• Cohesion two of your contacts have a close
  connection
• Structurally equivalent contacts contacts who
  link to the same third parties
• This more or less corresponds to the inverse of
  structural holes
• If two of your contacts are connected, you do not
  connect a structural hole
• If two of your contacts lead to the same other,
  then to get to that other, you actually would
  have needed only one of those contacts

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Structural holes vs network closure

• Empirical evidence on
• Dependent variable early promotion
• large bonus
• outstanding evaluation
• Most or all of the evidence seems to favor
  Burts structural holes
• Burt on Coleman
• Colemans dependent variable dropping out of
  school
• parents in a close network
• ? smaller probability of school dropout of
  children
• ? but parents may tend to earn less
• And about network closure
• Best team performance when groups are cohesive
  but team
• members have diverse external contacts.

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Structural holes vs network closure

• Coleman
• closure can overcome trust and cooperation
  problems
• (empirical evidence from data on school
  dropouts)
• Burt
• Structural holes give entrepreneurial
  possibilities
• (empirical evidence from data on US managers)
• Perhaps this is not so much a controversy after
  all ?
• There is a problem though, when it comes to
  innovation. For successful innovation one needs
  both to overcome trust and cooperation problems
  and entrepreneurial possibilities.

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Mark Granovetter The strength of weak ties

• Dept of Sociology, Harvard
• The strength of weak ties (1973)
• Granovetter was a sociology graduate student
  interviewed about 100 people who had changed jobs
  in the Boston area.
• More than half of the people found their new job
  through personal contacts (already at odds with
  standard economics).
• Many of these contacts were rather indirect (a
  weak tie)
• This is surprising, because strong ties are
  usually more willing to help you out
• Granovetters conjecture your strong ties are
  more likely to contain information you already
  know
• According to Granovetter you need a network that
  is low on transitivity

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Mark Granovetter The strength of weak ties
revisited

• You need weak ties because they give you better
  access to information
• Coser (1975) You need bridging weak ties weak
  ties that connect to groups outside your own
  clique ( you need cognitive flexibility, because
  you need to cope with heterogeneity of ties)
• Empirical evidence
• Granovetter (1974) 28 found job through weak
  ties
• 17 found job through strong ties
• Langlois (1977) showed this result depends on the
  kind of job
• Blau added arguments about high status people
  connecting to a more diverse set of people than
  low status people
• see Granovetters paper

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Mark Granovetterother work

• Granovetter is well known for the notion of
• (social) embeddedness
• all behavior occurs in a social structure, and
  that structure has
• influence on behavior.
• Institutional embeddedness
• shared rules and norms
• example two firms in an alliance, working under
  different judicial systems
• Temporal embeddedness
• the existence of past relations and anticipated
  future relations.
• example two firms in an alliance who have
  worked together before, vs not
• example two firms in an alliance who anticipate
  future dealings, vs not
• Structural embeddedness
• the existence of relations with third parties
• example two firms in an alliance have mutual
  customers, vs not

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Good theory should be portable

• COLEMAN
• Dependent variable school dropout
• Network actors pupils parents
• Network ties (frequency of) contact
• Closure leads to less dropouts
• BURT
• Dependent variable success in firms
• Network actors managers in a firm
• Network ties several kinds (see Burts paper)
• Managers with networks rich in structural holes
  do better.

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Good theory should be portable

• Dependent variable success in this class
• Network actors ?
• Network ties ?
• Students with which kinds of networks perform
  best? Based on which arguments?
• Dependent variable success of an RD-alliance
• Network actors ?
• Network ties ?
• Alliances with which kinds of networks perform
  best? Based on which arguments?
• Alternatives innovative succes of a department
  in a university
• innovativeness of the RD-department of a firm

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Read Coleman, Granovetter, and Burt

• Get acquianted with the research that was done in
  these papers
• Think about how the kinds of mechanisms as used
  in these papers can be useful for other problem
  formulations

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What will be next?

• ltsome more theory on social networksgt
• Closure, redundancy, structural holes, etc
• These can be made more concrete.

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The small world phenomenon Milgram (1967)

• Milgram sent packages to a couple hundred people
  in Nebraska and Kansas.
• Aim was get this package to ltaddress of person
  in Bostongt
• Rule only send this package to someone whom you
  know on a first name basis. Try to make the chain
  as short as possible.
• Result average length of chain is only six
• six degrees of separation. (we are all
  connected)
• Is this really true?
• Milgram used only part of the data, actually the
  ones supporting his claim
• Many packages did not end up at the Boston
  address
• Follow up studies all small scale

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The small world phenomenon (cont.)

• Small world project is testing this assertion
  as we speak (http//smallworld.columbia.edu), you
  can still participate
• Email to ltaddressgt, otherwise same rules.
  Addresses were American college professor, Indian
  technology consultant, Estonian archival
  inspector,
• Conclusion
• Low completion rate (384 out of 24163 1.5)
• Succesful chains more often through professional
  ties
• Succesful chains more often through weak ties
  (weak ties mentioned about 10 more often)
• Chain size 5, 6 or 7.

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The Kevin Bacon experiment Tjaden (/-1996)

• Actors actors Ties has played in a movie
  with
• Research implications of the small world
  phenomenon
• are not yet understood very well
• it leads to diffusion that is faster than
  expected (disease, innovation, fashion)
• And it may be good news for sustaining
  cooperation
• Small world networks have
• short average distance between pairs
• but relatively high cliquishness

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The Kevin Bacon game

• Can be played at
• http//www.cs.virginia.edu/oracle/
• Kevin Bacon
• number
• Rutger Hauer (NL) 2 Jackie Burroughs
• Famke Janssen (NL) 2 Donna Goodhand
• Kl.M. Brandauer (AU) 2 Robert Redford
• Arn. Schwarzenegger 2 Kevin Pollak
• Franka Potente (D) 2 Benjamin Bratt
• Marlene Dietrich (D) 2 Max. Schell
• Pascal Ulli (CH) 3 Felsenheimer, Lloyd
  Kaufman
• Bruno Ganz (CH) 2 Aidan Quinn

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How good a center is ?

• Average distance to other
• actors in Internet Movie db
• Rutger Hauer (NL) 2.81
• Famke Janssen (NL) 3.04
• Kl.M. Brandauer (AU) 2.96
• Arn. Schwarzenegger 2.87
• Franka Potente (D) 2.94
• Marlene Dietrich (D) 3.03
• Pascal Ulli (CH) 3.92
• Bruno Ganz (CH) 2.93
• Marc. Mastroianni (IT) 2.87
• Kevin Bacon 2.94
• Robert de Niro 2.77 at place 28
• Al Pacino 2.87

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The top 20 centers in the IMDB

• Steiger, Rod (2.67)
• Lee, Christopher (2.68)
• Hopper, Dennis (2.69)
• Sutherland, Donald (2.70)
• Keitel, Harvey (2.70)
• Pleasence, Donald (2.70)
• von Sydow, Max (2.70)
• Caine, Michael (I) (2.72)
• Sheen, Martin (2.72)
• Quinn, Anthony (2.72)
• Heston, Charlton (2.72)
• Hackman, Gene (2.72)
• Connery, Sean (2.73)
• Stanton, Harry Dean (2.73)
• Welles, Orson (2.74)
• Mitchum, Robert (2.74)
• Gould, Elliott (2.74)
• Plummer, Christopher (2.74)
• Coburn, James (2.74)

NB Bacon is at place 1049
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Elvis has left the building
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Connect the unconnectable
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Small world networks so what?

• You see it a lot around us for instance in road
  maps, food chains, electric power grids,
  metabolite processing networks, neural networks,
  telephone call graphs and social influence
  networks ? may be useful to study them
• We (can try to) create it
• see Hyves, openBC, etc
• They seem to be useful for a lot
• of things, and there are reasons
• to believe they might be useful
• for innovation purposes

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Social networking websites (sept06)