The document discusses social network analysis (SNA) as a multidisciplinary approach to mapping and measuring relationships among various entities such as individuals, organizations, and countries. It outlines SNA methods, applications, and various properties of networks, emphasizing its practicality in fields like sports and organizational dynamics. Additionally, it provides insight into using SNA to enhance collaboration and organizational productivity through understanding interactions and connections among network participants.

1. SOCIAL NETWORK ANALYSIS
PREM SANKAR C
DEPT OF FUTURES STUDIES
KERALA UNIVERSITY

2. “Think Link”
“Social relationships are hidden to
Real World”

3. DEFINITION
• Social network analysis (SNA) is a collection
of techniques, tools, and methods to map and
measure the relationships among people and
organizations
 SNA is multidisciplinary and deals with
 Sociology
 Graph theory
 Computer science
 Mathematics
 Economics
 Women Studies
 Development Studies

4. Actors (Nodes/ Vertices)
 Actors –are the smallest unit of a network
 Persons
 Organizations
 Countries
 Companies
 Animals
 Words
 Web pages
 Families

5. D
e
Relations (Link/Edge/Tie/Arc)
p
t
o Two Actors are connected
f by a social relationship.
Affective
F
likes, trusts
u Kinship
t
mother of, wife of
 Interactions
u
give advice, talks to, fights
r  Other role-based
with, lends money to
e
boss of, teacher of
sex / drugs with
friend of
s
S
• Affiliations
t Cognitive/perceptual
belong to same clubs /
knows
u
companies
aware of what they know
d
is physically near
i
e

6. D
e
p
t
o
f
F
u
t
u
r
e
s
S
t
u
d
i
e
Type of Relations
Relations can be
Undirected
Directed
Weighted
Weight can be
Strength
Rank
Frequency
Probability

7. SNA Method in a Nutshell
Step
Activities/Tools
Design
Identify boundaries
Clarify and design questions
Collect Data
Surveys
Interviews
Facebook, LinkedIn
Email logs
Analyze data to generate
maps and metrics
(Pajek/UCINET, NodeXL, Gephi
… many others)
Review data
Validate; look for questions
Prepare evaluation
Match network results with
context and stories
Move into action
Weaving & other interventions
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8. 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
•Sentimental analyis
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9. Expected Research Types
• Assess the network’s capacity for collaboration,
information transfer, technology diffusion etc.
• Identify potential relationships among people based on
shared events, meetings, ideas, or areas of expertise
• Identify key individuals - positions of individuals in
the network
– # of connections
– Favorability of position
• Identifying people who are well positioned to influence
the network or to move information around
• Comparing groups within networks or for comparing
changes in a network over time (Dynamics Study)

10. PRACTICAL
APPLICATIONS OF SNA...
helping you see your
interconnected world

11. Network Applications







Citation network
Coauthership network
Terrorist networks
Economic networks
Family Networks
Organization networks
Sports Networks
A
Is related to
B
Patterns are
left behind

12. SNA for Sports
all about
connections
from people
to people

13. Network Analysis in Cricket
• Most connected one is not necessarily the most
central and most central players are not
necessarily the one with high performance one.
• Quantifying individual performance in Cricket
−Relative importance and effect of removing a
player from the team, based on different centrality
scores.
Social Network Analysis as a tool to
analyze interaction of Batsmen and
Bowlers in Cricket

14. Organizational Network Analysis
• ONA is a method for studying communication and
socio-technical networks within an organization.
• Organizational network analysis (ONA) often refers
to the use of SNA methods in the context of
organization dynamics and development
• It is a quantitative descriptive technique for creating
statistical and graphical models of the people, tasks,
groups, knowledge and resources of organizational
systems

15. To Find Subject Matter Experts
• Each node indicates people working in particular
domain area .
• X --> Y means X seeks knowledge from Y.
• Two people are connected if one goes to the other
for expertise in this domain .
• Potential of each node is shown in different colors
based on their experience.

16. Maximizing Organizational Productivity
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
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 Organizations.
Harvard Business School Press.
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17. Broader Applications of SNA
Accelerate diffusion by identifying opinion leaders
Reveal how infections spread among patients and staff in a hospital
Map executive's personal network based on email flows
Map interactions amongst blogs on various topics
Map communities of expertise in various fields
Discover emergent communities of interest amongst faculty at various
universities
Discover useful patterns in click streams on the WWW
Viral spread: disease, fads and fashions, ideas, YouTube videos
To Find Subject Matter Experts in Particular Area
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Source: http://www.orgnet.com/sna.html

18. What’s the Moral of the Story?
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19. Political blogs

20. Organizations

21. Facebook networks

22. Ingredient networks

23. Thank You
Are you interested in Social Network
Analysis ?
Feel Free to contact me
On
9846924006 or
prems4u@gmail.com
Source: http://www.orgnet.com/sna.html
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