This document provides an introduction to social network analysis. It discusses how networks can be mapped and analyzed using tools to understand their structure and flow of information. Key aspects of network analysis are introduced, including nodes, ties, centrality metrics, and structural patterns. A variety of tools are presented, ranging from free social media applications to specialized software, that can be used to map and analyze networks. The value of network analysis is in identifying influential individuals, improving collaboration and knowledge sharing, and intervening to change network structures and behaviors.

1. Social Network Analysis
Patti Anklam
Columbia IKNS 4305 Unit 3
April 2013

2. I’ve become convinced that understanding
how networks work is an essential 21st
century literacy.
Howard Rheingold

3. Columbia IKNS Residency April 2013
Agenda
―The language of networks
―Networks in organizations
3
Social Network Analysis
Introduction to tools for
social, organizational,
and personal network
analysis

4. The New Language of Networks
http://www.dftdigest.com/images/Spyglass.jpg

5. We live in networks all the time
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• We live in networks all the time:
communities, organizations,
teams
• There is science to support the
understanding of network
structure
• The structure of a network
provides insights into how the
network “works”
• Once you understand the
structure, you can make
decisions about how to manage
the network’s context
• Network analysis tools help you
understand the structure

6. Columbia IKNS Residency April 2013
The Premise: Networks Matter
• The complexity of work in today’s
world is such that no one can
understand – let alone complete – a
task alone
– Individual-individual
– Team-team
– Company-company
– Eco-system to eco-system
• Strong networks are correlated with health:
– People with stronger personal networks are more productive, happier,
and better performers
– Companies who know how to manage alliances are more flexible,
adaptive and resilient
– Our personal health and well-being is often tied to our social networks
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7. Columbia IKNS Residency April 2013
The Importance of Understanding Networks
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8. Columbia IKNS Residency April 2013
The new science of networks
• Beginning in the 1990’s computer
science made it possible to map and
analyze large social networks.
2002
2002
2002
2003
2004
2004
2009
2009
• By 2009, network
science and analysis
are accepted practice
in science and
management
• Insights
became
accessible to
the public.
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9. Network Perspective
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• If it’s a network, you can map it:
– People-people
– Group-group
– Within organizations
– Across organizations
• A network is a collection of entities linked by a type of
relationship
• All networks have common properties and can be analyzed
– Information artifacts
– Ideas & issues
Node
Tie

10. Columbia IKNS Residency April 2013
Rob Cross’s Classic Case
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From: The OrganizationalNetwork Fieldbook,Rob Cross et al, Jossey-Bass 2010

11. Columbia IKNS Residency April 2013
A Classic Case
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From: The OrganizationalNetwork Fieldbook,Rob Cross et al, Jossey-Bass 2010

12. Columbia IKNS Residency April 2013
A Classic Case
From: The Hidden Power of SocialNetworks, Rob Cross and Andrew Parker, Harvard Business School Press, 2004
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From: The OrganizationalNetwork Fieldbook,Rob Cross et al, Jossey-Bass 2010

13. Columbia IKNS Residency April 2013
A Classic Case
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From: The OrganizationalNetwork Fieldbook,Rob Cross et al, Jossey-Bass 2010

14. Columbia IKNS Residency April 2013
A Classic Case
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From: The OrganizationalNetwork Fieldbook,Rob Cross et al, Jossey-Bass 2010

15. Columbia IKNS Residency April 2013
It’s all about Questions
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Patterns provide
insights that provoke
good questions.
Full stop.

16. Columbia IKNS Residency April 2013
Map Patterns
Multi-Hub Hub and Spoke
Stove-piped (Siloed) Core/Periphery
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17. The Unit of Analysis: The Relationship
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18. Different Questions, Different Maps
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“I interact with this person somewhat
frequently”
“I understand this person’s knowledge and
skills “ (Agree or Strongly Agree)

19. • Look at the whole network
and its components
Network Analysis Also Provides Metrics
• Look at positions of
individuals in the network
Centrality Metrics
Structural Metrics
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20. Structural Metrics
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• Common measures:
–Density of interactions
–Average degree of separation
–Cross-group or cross-organization
connectivity
• Good for comparing questions,
groups within networks or for
comparing changes in a network
over time
Look at the whole network and its components

21. Interpreting Results
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“I interact with this person twice a month
or more”
I understand this person’s knowledge and
skills (Agree or Strongly Agree)
Density: 11%
Distance: 2.7
Density: 28%
Distance: 1.8

22. How the Metrics Enhance the Maps
2010
2011
Year # Density Avg #
ties
2009 55 2.2% 1.2
2010 90 2.7% 2.4
2011 85 5.3% 4.5
2012 82 8% 6.88
2009
2012
22

23. Centrality Metrics
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Look at positions of individuals in the network
• Good for identifying people who are well
positioned to influence the network or
to move information around
• Common measures:
–Number of connections
–Frequency of occurrence on paths
between others
–Diversity of connections

24. Identifying Key People
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Who are the people who are best positioned to move information through the network?
In-degree: 16
Betweenness: 1125
In-degree: 5
Betweenness: 586
In-degree: 11
Betweenness: 469
In-degree: 9
Betweenness: 415

25. Columbia IKNS Residency April 2013
Positional Sleuthing in ONA
• Based on this data:
• Who should Jerry
appoint as his
successor?
• Who do you think Jerry
actually appointed as
his successor? Why?
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26. Columbia IKNS Residency April 2013
AB
DG
KF
KS
MK
NM
NS
PM
PP
RC
RR
SK
Diversity
• Organization
• Expertise
• Age, Tenure
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AB
AL
BG
DC
GP
MB
PM
SA
• Social Ties
• Geographic location
• Hierarchical position

27. The Importance of Diversity
People who live in the intersection of social
worlds are at higher risk of having good ideas. –
Ron Burt
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28. Columbia IKNS Residency April 2013
Detecting Diversity
• Who is more likely to have
access to new ideas?
– Tom
– Marion
• Why?
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29. Columbia IKNS Residency April 2013
KM Interventions
Ways to change patterns in
networks
Practices from the KM Repertoire
Create more connections Make introductions through meetings and webinars, face-to-face events
(like knowledge fairs); implement social software or social network
referral software; social network stimulation
Increase the flow of knowledge Establish collaborative workspaces, install instant messaging systems,
make existing knowledge bases more accessible and usable
Discover connections Implement expertise location and/or; discovery systems; social
software; social networking applications
Decentralize Social software; blogs, wikis; shift knowledge to the edge
Connect disconnected clusters Establish knowledge brokering roles; expand communication channels
Create more trusted relationships Assign people to work on projects together
Alter the behavior of individual nodes Create awareness of the impact of an individual’s place in a network;
educate employees on personal knowledge networking
Increase diversity Add nodes; connect and create networks; encourage people to bring
knowledge in from their networks in the world
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30. Organizational Networks Summary
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• The science of networks has brought insights into the structure
of organizational networks
• Organizational network analysis lets us map relationships that
reveal the informal networks through which work gets done
• Developing and sharing these maps helps organizations
improve collaborative capacity, overcome obstacles to
effective sharing, and redesign their work relationships
• Results are a guide to asking good questions and should never
be interpreted as an “answer”

31. Introduction to Organizational, Social,
and Network Analysis Tools
http://quilting.about.com/od/picturesofquilts/ig/Alzheimer-s-Quilts/The-Ties-that-Bind.htm

32. Basic Terminology
• Node: an individual person in the
network. Sometimes called a vertex.
• Tie: a relationship between two
nodes. Sometimes called a link,
sometimes an edge.
• Ties are either directed, in which
case the arrows provide “from – to”
information, or undirected
• The complete set of nodes and ties
is often called the social graph, or
simply the graph
Nodes and ties: the graph

33. Basic Terminology
• Degree: The number of ties a node
has is its degree, which can be
distinguished between in-degree
and out-degree.
Node B has an in-degree of 4. Node
E has an out-degree of 2
• Path: The sequence of ties and
nodes between one node and
another.
Node D has two paths to Node C
• Path length: number of degrees
between two nodes. Often called
the distance between two nodes.
Paths and degrees

34. Columbia IKNS Residency April 2013
Basics of Network Map
Core
Periphery
Isolates
Structural Hole
Cluster

35. Math Behind the Science
• Relationships (ties) among people
(nodes) can be analyzed:
– Distances between nodes (and
averages)
– Centrality of nodes
– Average density of interactions
• Mathematical formulas identify
patterns, clusters, cliques

36. What Sorts of Tools Are There?
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• Range in complexity of
function & cost
• Let you access and map
your own network
Social Media
Applications
Tools Designed for
SNA/ONA
Specialized assessment
instruments
• PNA (personal network
assessment) tool offers
individualized results

37. Mapping and Analysis Tools

38. Tool Basics – The Questions
• Improve collaboration
• Finding connectors and
influencers in organizations and
communities
• Leadership development
• Performance benchmarking
• Integration of units following
merger/acquisition
Problem (Examples) Relationships of Interest
• Access to expertise
• Innovative & capacity
• Collaborative capacity
• Ease of knowledge flow
• Decision-making and task flow
• Innovation potential
• Energy
Shares new ideas with
Seeks help for problem-solvingWorks closely with
Knows expertise of
Questions: the art of the network analysis

39. Tool Basics – the Dataset
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Information about the nodes (vertices) and the ties (edges)

40. Load and Draw…
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41. Short List of Resources for SNA/ONA Tools
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http://tinyurl.com/SNA-ONA-Tools

42. Columbia IKNS Residency April 2013
Network Insights Don’t Require Fancy Software
• If it’s a network, you can draw it.
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43. Columbia IKNS Residency April 2013
Our Networks and Social Media
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http://inmaps.linkedinlabs.com/

44. Columbia IKNS Residency April 2013
Where’s Kate?
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45. Columbia IKNS Residency April 2013
Facebook
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46. Columbia IKNS Residency April 2013
Understanding Your Personal Network
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Focus Purpose How to Develop
Operational Getting work done
efficiently
Identify people who can
block or support a
project
Personal Develop and maintain
professional skills and
reputation
Participate in
professional
associations, clubs, and
physical and online
communities
Strategic Figure out and obtain
support for future
priorities and challenges
Identify lateral and
vertical relationships
outside your immediate
control
Source: “How Leaders Create and Use Networks,” Herminia Ibarra and Mark Hunter, Harvard Business Review January 2007

47. Columbia IKNS Residency April 2013
The PNA (Personal Network Assessment)
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48. Columbia IKNS Residency April 2013
Summary
• Social network analysis tools and methods are available to map
organizational as well as the individual’s personal network
• The tools matter less than the network mindset – and the understanding
that the structure of a network matters
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49. Question
• patti@pattianklam.com
•http://www.pattianklam.com
Thank you.
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