Transcript Social Network Analysis - OpenCourseWare

Social Network Analysis and
Knowledge Management
KM 631
April 28, 2007
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Outline
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Overview of SNA and it's relation to KM
Broad applications of SNA
Application of SNA to KM
SNA basics using Kite diagram
Class examples - UCLA and Mgt 631
Going beyond structure - Study of Trust at HP
Personality and social networks
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Definitions
• Knowledge Management: the range of practices used by
organizations to identify, create, represent and distribute
knowledge for reuse, awareness, and learning across the
organizations.
• Social Network Analysis: The mapping and measuring of
relationships and flows of information between people,
organizations, computers, or other information or
knowledge processing entities.
– Nodes are people and groups; links show relationships or flows
between the nodes
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Source: Krebs & Associates
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Revealing Book Networks
http://www.orgnet.com/booknet.html
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Political Books and Polarized
Readers?
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World Trade
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SNA of the 9-11 Terrorist Network
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Social Network Theory
is related to…
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Social capital
Network effect
Diffusion of innovations
Complexity theory (butterfly effect, swarm theory)
Small world phenomenon, six degrees of
separation
• Online social networks (Facebook, Linked-In)
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Networks Are Critical to
Innovation Diffusion
later
adopters
100%
Successful innovation
Percent of
Adopters
“critical mass”
20%
Unsuccessful innovation
- “island of innovation”
- diffuse or die phenomenon
early
adopters
Time
Rogers, E. (1995). The Diffusion of 12
Innovations. New York: The Free Press
Diffusion Using Opinion Leaders
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IT-Enabled Networking
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Using E-Mail to Identify Optimal Paths
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Broader Applications of SNA
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Reveal how infections spread
among patients and staff in a
hospital
Accelerate diffusion by identifying
opinion leaders
Improve the innovation of a group
of scientists and researchers
Find emergent leaders in fast
growing company
Map executive's personal network
based on email flows
Analyze book selling patterns to
position a new book
Analyze terrorist networks
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Map interactions amongst blogs
on various topics
Map communities of expertise in
various medical fields
Examine a network of farm
animals to analyze how disease
spreads from one cow to another
Map network of Jazz musicians
based on musical styles and CD
sales
Discover emergent communities of
interest amongst faculty at various
universities
Discern useful patterns in click
streams on the WWW
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Source: http://www.orgnet.com/sna.html
Application of SNA to People and
Organizations
Career Planning
How do people find jobs?
Mergers and
Acquisitions
Is the cross-border M&A working?
Business Process
Re-engineering
Where are the organizational disconnects?
Where are the bottlenecks?
Human Resources
Are any groups isolated? (e.g., young engineers)
Are diversity efforts working?
Organizational
Design
How should the office be laid out?
Knowledge
Management
How do innovations spread?
Who are the resident Subject Matter Experts?
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Your Network Structure Matters
• Social networks that are large, diverse, rich in weak ties
and “structural holes” lead to a range of positive
outcomes including:
– Access to novel sources of information (Granovetter, 1973)
– Fruitful inventions and career advancement (Burt, 1992)
– Discovery of new jobs (Granovetter, 1993)
• Social networks that are small, dense, rich with strong
ties leads to:
– Increased accessibility (Baker, 1993)
– Help with resource mobilization (Obstfeld, 2005)
– Protection in times of danger or uncertainty (1992)
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Three Common Organizational Communication
Networks and How They Rate on Effectiveness
Criteria
depends
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The Kite Diagram
Who is most “central”?
Most “between”?
Most “close”?
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Centrality Measures
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Local Centrality (Degree): The number of links an actor has with other
actors.
• A potential sign of power
• High in-degree can be a sign of prominence or prestige
• High out-degree can be a sign of influence
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Betweeness: The degree to which an actor is situated between two
groups, and is a necessary route between those groups.
• Actors with high betweeness have the potential to have a major influence
• They can be mediators/brokers, gatekeepers, bottlenecks, or obstacles to
communication
• They are especially valuable when the link two diverse groups
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Global Centrality (Closeness): the average distance between an actor
and all other actors in a network.
• Most likely to be “in the know” about what is happening
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Adjacency Matrix for Kite Diagram
Andre
Andre
Beverly
Beve
rly
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1
1
Garth
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Fernando
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Carol
1
Diane
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Ike
Jane
Garth
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Ed
Heather
Ed
Fer
nando
Carol
Diane
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1
1
1
1
1
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1
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1
Heat
her
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1
1
1
Ike
Jane
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1
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1
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Three Ways to Gather Data
• Closed Network (Positional) Approach
– Researcher studies connections between
closed, known network
• Ego (Reputational) Approach
– Researcher studies those named on ego’s list
• Snowball Method
– Researcher asks ego to nominate others and
follows chain
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Six Varieties of Knowledge
Networks
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Work Network
– With whom do you exchange information as part of your daily work routines?
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Social Network
– With whom do you “check in” inside and outside the office to find out what is
going on?
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Innovation Network
– With whom do you collaborate or kick around new ideas?
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Expert Knowledge Network
– Whom do you turn to for expertise or advice about the enterprise?
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Career Guidance or Strategic Network
– Whom do you go to for advice about your future?
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Learning Network
– Whom do you work with to improve existing processes or methods?
Source: http://www.well.com/~art/s+b42002cm.html
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UCLA ELP Class Social Network
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UCLA ELP Class Social Network
Node Size = Centrality
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UCLA ELP Class Social Network
Node Size = Betweeness
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UCLA ELP Class Expert Network
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UCLA ELP Class Expert Network
Node Size = Centrality
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UCLA ELP Class Expert Network
Node Size = Betweeness
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KM 631 “Acquaintance” Network
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KM 631 “School” Network
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KM 631 “Social” Network
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KM 631 “Acquaintance” Network – Reciprocal Ties
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KM 631 “School” Network – Reciprocal Ties
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KM 631 “Social” Network – Reciprocal Ties
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KM 631 Class “Social” Network
Node Size = Centrality
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What’s the Moral of the Story?
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Categories of Network Properties
Structural (quantitative)
•Size
•Density
•Diversity
•Structural Holes
•Isolates/Cliques
•Centrality
•Betweeness
•Closeness
Relational (qualitative)
•Strength of ties
•Accessibility
•Likeability/”fun”
•Reputation
•Expected reciprocity?
•Competing unit?
•Dependence
•Trust
Individual (qualitative)
•Personality (e.g., Big 5,
self-monitoring)
•Emotional intelligence
•Intentionality
•Past experience
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Maximizing Network Support and Productivity
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How valuable is the information I receive from this person?
How well does this person collaborate with me to solve problems and make decisions?
How aware is this person of my skills?
How accessible is this person to me?
How “engaged” is this person with me?
How safe is it to communicate with this person?
What is the level of quality of conversation with this person?
To what degree is my productivity improved by this person?
How much power and influence does this person have?
How much do I like this person?
To what degree does this person support the achievement of my career goals?
To what degree does this person support the achievement of my personal goals?
To what degree does this person energize (or exhaust) me?
To what degree do I trust this person?
• Evaluate each person in your network
• Be evaluated by each person in your network!
• Best conducted as 360 by 3rd party, NOT managers
Source: Robert Cross & Andrew Parker (2004), The Hidden Power of Social Networks: How Work Really Gets Done in
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Organizations. Harvard Business School Press.
Trust Is…
• one’s willingness to become vulnerable to another party
in order to achieve some expected gain even when one
is unable to control or monitor the other party (Mayer et
al., 1995).
• the “essential lubricant,” that enables cooperation and
social exchange (Cohen and Prusak, 2001:28, Barber,
1983; Hardin, 1996; Luhmann, 1979).
• At least minimum levels of trust are required for
individuals to activate and use the contacts in their
networks (Rousseau et al., 1998)
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Components of Trust
• Competence: Being an expert in the
subject matter I seek
• Benevolence: Having my best interests
at heart
• Integrity: Ethical behavior or alignment
with my value system
Source: Mayer, R., Davis, J. and Schoorman, F. (1995). An integrative model
of organizational trust. Academy of Management Review, July, Vol. 20, No. 3,
pp. 709-734
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HP Study
• Sample: 50 senior leaders at HP (SVPs, VPs, Directors, GMs) yielding
data on 661 contacts
• Who do you go to for:
– Actionable advice: Suggestions or recommendations to help you
succeed
– Political help: Assistance with thinking strategically
– Emotional support: A sympathetic ear
– Raw information: Facts, figures, date and numbers that help you
get work done
• Please rate this person in terms of:
– Competence
– Benevolence
– Integrity
• How big a difference has this person’s advice made to your success?
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Whom Would You Choose To Work With?
Faced with the need to accomplish a task at work, what sort of person would you pick to help you?
Studies showed that most people would choose a “lovable fool” over a “competent jerk”.
Source: Casciaro, T & Lobo, S. (2005). Competent Jerks, Lovable Fools and the Formation of Social Networks. HBR
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Correlations Between Element of Trust
and Type of Support Sought
Type of Support
Competence Benevolence Integrity
Seek actionable advice
.197**
.209**
.198**
Seek emotional support
-.009
.369**
.243**
Seek political or strategic
assistance
.126**
.108*
.114**
Seek raw information
-.086*
-.144**
-.136**
N = 660 contacts from 50 executives
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Variations of Trust and Difference Made in
Career Success
Avg Diff Made
2.5
2
1.5
Avg Diff Made
1
0.5
0
Competence
Benevolence
Integrity
N
L
L
H
H
H
H
L
L
L
H
L
H
L
H
L
L
H
H
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52
63
62
166
256
Note: C, B, I dichotomized into L+M = L, H=H
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Big Five Personality Traits
• Extroversion
(warmth, gregariousness, assertiveness, activity,
excitement-seeking, positive emotions)
• Agreeableness
(trust, straightforwardness, altruism, compliance,
modesty, tender-mindedness)
• Conscientiousness
(competence, order, dutifulness,
achievement-striving, self-discipline, deliberation)
• Neuroticism
(anxiety, anger, depression, self-consciousness,
impulsiveness, vulnerability)
• Openness to Experience
(fantasy, aesthetics, feelings,
actions, ideas, values)
Source: Costa & McCrae, 1992, NEO PI-R Professional Manual
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Correlations Between Personality Traits and
Social Network Structure
Individual
Attribute
Extroversion
Network
Size
Strength of
Ties
Trust
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+
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Agreeableness
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Conscientiousness
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Neuroticism
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Openness to
Experience
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Networking
Intentionality
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Density
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-+
Diversity
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+
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