Social Network Analysis

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Social Network Analysis and Knowledge Management

KM 631 April 28, 2007 1

Outline

• 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 2

Definitions

• Knowledge Management organizations.

: the range of practices used by organizations to identify, create, represent and distribute knowledge for reuse, awareness, and learning across the • 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 3

Source: Krebs & Associates 4

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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 9

SNA of the 9-11 Terrorist Network

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Social Network Theory is related to…

• 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) 11

100%

Networks Are Critical to Innovation Diffusion

later adopters

Successful innovation

Percent of Adopters “critical mass”

Unsuccessful innovation

“island of innovation” - diffuse or die phenomenon 20% 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 15

Broader Applications of SNA

• 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 • 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 16 Source: http://www.orgnet.com/sna.html

Application of SNA to People and Organizations

Career Planning Mergers and Acquisitions Business Process Re-engineering Human Resources Organizational Design Knowledge Management

How do people find jobs?

Is the cross-border M&A working?

Where are the organizational disconnects?

Where are the bottlenecks?

Are any groups isolated? (e.g., young engineers) Are diversity efforts working?

How should the office be laid out?

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) 18

Three Common Organizational Communication Networks and How They Rate on Effectiveness Criteria depends 19

The Kite Diagram

Who is most “central”?

Most “between”?

Most “close”?

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Centrality Measures

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 • 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 • 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 21

Adjacency Matrix for Kite Diagram

Andre Beverly Ed Garth Fernando Carol Diane Heather Ike Jane Andre Beve rly 1 1 1 1 1 1 1 1 Ed 1 1 1 Garth 1 1 1 1 1 Fer nando 1 Carol 1 1 1 Diane 1 1 1 1 1 1 1 1 1 1 Heat her 1 1 1 Ike Jane 1 1 1 22

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 23

Six Varieties of Knowledge Networks

• Work Network – With whom do you exchange information as part of your daily work routines?

• Social Network – With whom do you “check in” inside and outside the office to find out what is going on?

• Innovation Network – With whom do you collaborate or kick around new ideas?

• Expert Knowledge Network – Whom do you turn to for expertise or advice about the enterprise?

• Career Guidance or Strategic Network – Whom do you go to for advice about your future?

• 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 25

UCLA ELP Class Social Network Node Size = Centrality 26

UCLA ELP Class Social Network Node Size = Betweeness 27

UCLA ELP Class Expert Network 28

UCLA ELP Class Expert Network Node Size = Centrality 29

UCLA ELP Class Expert Network Node Size = Betweeness 30

KM 631 “Acquaintance” Network 31

KM 631 “School” Network 32

KM 631 “Social” Network 33

KM 631 “Acquaintance” Network – Reciprocal Ties 34

KM 631 “School” Network – Reciprocal Ties 35

KM 631 “Social” Network – Reciprocal Ties 36

KM 631 Class “Social” Network Node Size = Centrality 37

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 39

Maximizing Network Support and Productivity 1.

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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 networkBe evaluated by each person in your network!Best conducted as 360 by 3

rd party, NOT managers

Source: Robert Cross & Andrew Parker (2004), The Hidden Power of Social Networks: How Work Really Gets Done in 40 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) 41

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 42

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 44

Correlations Between Element of Trust and Type of Support Sought

Type of Support Seek actionable advice Seek emotional support Seek political or strategic assistance Seek raw information

Competence Benevolence Integrity

.197** -.009

.126** -.086* .209** .369** .108* -.144** .198** .243** .114** -.136** N = 660 contacts from 50 executives 45

Variations of Trust and Difference Made in Career Success Avg Diff Made 2.5

2 1.5

1 0.5

0 Competence Benevolence Integrity N L L L 44 L L H 52 H L L 63 Note: C, B, I dichotomized into L+M = L, H=H H H L 62 H L H 166 H H H 256 Avg Diff Made 46

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 47

Correlations Between Personality Traits and Social Network Structure

Individual Attribute

Extroversion Network Size

+

Strength of Ties

+

Trust

+

Density Diversity

+

Agreeableness

+

Conscientiousness Neuroticism Openness to Experience Networking Intentionality

+ + + + + - +

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