Social Network Analysis & an Introduction to Tools

Patti Anklam
Patti AnklamNetworks and Knowledge Management at Net Work
Social Network Analysis
Patti Anklam
Columbia IKNS 4305 Unit 3
April 2013
I’ve become convinced that understanding
how networks work is an essential 21st
century literacy.
Howard Rheingold
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
The New Language of Networks
http://www.dftdigest.com/images/Spyglass.jpg
We live in networks all the time
5
• 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
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
6
Columbia IKNS Residency April 2013
The Importance of Understanding Networks
7
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.
8
Network Perspective
9
• 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
Columbia IKNS Residency April 2013
Rob Cross’s Classic Case
10
From: The OrganizationalNetwork Fieldbook,Rob Cross et al, Jossey-Bass 2010
Columbia IKNS Residency April 2013
A Classic Case
11
From: The OrganizationalNetwork Fieldbook,Rob Cross et al, Jossey-Bass 2010
Columbia IKNS Residency April 2013
A Classic Case
From: The Hidden Power of SocialNetworks, Rob Cross and Andrew Parker, Harvard Business School Press, 2004
12
From: The OrganizationalNetwork Fieldbook,Rob Cross et al, Jossey-Bass 2010
Columbia IKNS Residency April 2013
A Classic Case
13
From: The OrganizationalNetwork Fieldbook,Rob Cross et al, Jossey-Bass 2010
Columbia IKNS Residency April 2013
A Classic Case
14
From: The OrganizationalNetwork Fieldbook,Rob Cross et al, Jossey-Bass 2010
Columbia IKNS Residency April 2013
It’s all about Questions
15
Patterns provide
insights that provoke
good questions.
Full stop.
Columbia IKNS Residency April 2013
Map Patterns
Multi-Hub Hub and Spoke
Stove-piped (Siloed) Core/Periphery
16
The Unit of Analysis: The Relationship
17
Different Questions, Different Maps
18
“I interact with this person somewhat
frequently”
“I understand this person’s knowledge and
skills “ (Agree or Strongly Agree)
• 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
19
Structural Metrics
20
• 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
Interpreting Results
21
“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
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
Centrality Metrics
23
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
Identifying Key People
24
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
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?
25
Columbia IKNS Residency April 2013
AB
DG
KF
KS
MK
NM
NS
PM
PP
RC
RR
SK
Diversity
• Organization
• Expertise
• Age, Tenure
26
AB
AL
BG
DC
GP
MB
PM
SA
• Social Ties
• Geographic location
• Hierarchical position
The Importance of Diversity
People who live in the intersection of social
worlds are at higher risk of having good ideas. –
Ron Burt
27
Columbia IKNS Residency April 2013
Detecting Diversity
• Who is more likely to have
access to new ideas?
– Tom
– Marion
• Why?
28
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
29
Organizational Networks Summary
30
• 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”
Introduction to Organizational, Social,
and Network Analysis Tools
http://quilting.about.com/od/picturesofquilts/ig/Alzheimer-s-Quilts/The-Ties-that-Bind.htm
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
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
Columbia IKNS Residency April 2013
Basics of Network Map
Core
Periphery
Isolates
Structural Hole
Cluster
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
What Sorts of Tools Are There?
36
• 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
Mapping and Analysis Tools
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
Tool Basics – the Dataset
39
Information about the nodes (vertices) and the ties (edges)
Load and Draw…
40
Short List of Resources for SNA/ONA Tools
41
http://tinyurl.com/SNA-ONA-Tools
Columbia IKNS Residency April 2013
Network Insights Don’t Require Fancy Software
• If it’s a network, you can draw it.
42
Columbia IKNS Residency April 2013
Our Networks and Social Media
43
http://inmaps.linkedinlabs.com/
Columbia IKNS Residency April 2013
Where’s Kate?
44
Columbia IKNS Residency April 2013
Facebook
45
Columbia IKNS Residency April 2013
Understanding Your Personal Network
46
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
Columbia IKNS Residency April 2013
The PNA (Personal Network Assessment)
47
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
48
Question
• patti@pattianklam.com
•http://www.pattianklam.com
Thank you.
49
1 of 49

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Social Network Analysis & an Introduction to Tools

  • 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 5 • 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 6
  • 7. Columbia IKNS Residency April 2013 The Importance of Understanding Networks 7
  • 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. 8
  • 9. Network Perspective 9 • 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 10 From: The OrganizationalNetwork Fieldbook,Rob Cross et al, Jossey-Bass 2010
  • 11. Columbia IKNS Residency April 2013 A Classic Case 11 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 12 From: The OrganizationalNetwork Fieldbook,Rob Cross et al, Jossey-Bass 2010
  • 13. Columbia IKNS Residency April 2013 A Classic Case 13 From: The OrganizationalNetwork Fieldbook,Rob Cross et al, Jossey-Bass 2010
  • 14. Columbia IKNS Residency April 2013 A Classic Case 14 From: The OrganizationalNetwork Fieldbook,Rob Cross et al, Jossey-Bass 2010
  • 15. Columbia IKNS Residency April 2013 It’s all about Questions 15 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 16
  • 17. The Unit of Analysis: The Relationship 17
  • 18. Different Questions, Different Maps 18 “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 19
  • 20. Structural Metrics 20 • 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 21 “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 23 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 24 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? 25
  • 26. Columbia IKNS Residency April 2013 AB DG KF KS MK NM NS PM PP RC RR SK Diversity • Organization • Expertise • Age, Tenure 26 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 27
  • 28. Columbia IKNS Residency April 2013 Detecting Diversity • Who is more likely to have access to new ideas? – Tom – Marion • Why? 28
  • 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 29
  • 30. Organizational Networks Summary 30 • 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? 36 • 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
  • 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 39 Information about the nodes (vertices) and the ties (edges)
  • 41. Short List of Resources for SNA/ONA Tools 41 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. 42
  • 43. Columbia IKNS Residency April 2013 Our Networks and Social Media 43 http://inmaps.linkedinlabs.com/
  • 44. Columbia IKNS Residency April 2013 Where’s Kate? 44
  • 45. Columbia IKNS Residency April 2013 Facebook 45
  • 46. Columbia IKNS Residency April 2013 Understanding Your Personal Network 46 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) 47
  • 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 48