SlideShare a Scribd company logo
1 of 23
SOCIAL NETWORK ANALYSIS

PREM SANKAR C
DEPT OF FUTURES STUDIES
KERALA UNIVERSITY
“Think Link”

“Social relationships are hidden to
Real World”
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
Actors (Nodes/ Vertices)
 Actors –are the smallest unit of a network
 Persons
 Organizations
 Countries
 Companies
 Animals
 Words
 Web pages
 Families
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
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
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
7
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

8
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)
PRACTICAL
APPLICATIONS OF SNA...
helping you see your

interconnected world
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
SNA for Sports

all about
connections
from people
to people
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
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
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.
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.
16
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

17

Source: http://www.orgnet.com/sna.html
What’s the Moral of the Story?

18
Political blogs
Organizations
Facebook networks
Ingredient networks
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

24

More Related Content

What's hot

What's hot (20)

Community detection in social networks
Community detection in social networksCommunity detection in social networks
Community detection in social networks
 
Network measures used in social network analysis
Network measures used in social network analysis Network measures used in social network analysis
Network measures used in social network analysis
 
CS6010 Social Network Analysis Unit V
CS6010 Social Network Analysis Unit VCS6010 Social Network Analysis Unit V
CS6010 Social Network Analysis Unit V
 
Social Network Analysis
Social Network AnalysisSocial Network Analysis
Social Network Analysis
 
Social Network Visualization 101
Social Network Visualization 101Social Network Visualization 101
Social Network Visualization 101
 
Social Network Analysis (SNA)
Social Network Analysis (SNA)Social Network Analysis (SNA)
Social Network Analysis (SNA)
 
CS6010 Social Network Analysis Unit I
CS6010 Social Network Analysis Unit ICS6010 Social Network Analysis Unit I
CS6010 Social Network Analysis Unit I
 
Community Detection in Social Networks: A Brief Overview
Community Detection in Social Networks: A Brief OverviewCommunity Detection in Social Networks: A Brief Overview
Community Detection in Social Networks: A Brief Overview
 
Social Network Analysis
Social Network AnalysisSocial Network Analysis
Social Network Analysis
 
Social Media Mining - Chapter 3 (Network Measures)
Social Media Mining - Chapter 3 (Network Measures)Social Media Mining - Chapter 3 (Network Measures)
Social Media Mining - Chapter 3 (Network Measures)
 
Community Detection in Social Media
Community Detection in Social MediaCommunity Detection in Social Media
Community Detection in Social Media
 
Network Visualization guest lecture at #DataVizQMSS at @Columbia / #SNA at PU...
Network Visualization guest lecture at #DataVizQMSS at @Columbia / #SNA at PU...Network Visualization guest lecture at #DataVizQMSS at @Columbia / #SNA at PU...
Network Visualization guest lecture at #DataVizQMSS at @Columbia / #SNA at PU...
 
Graph Representation Learning
Graph Representation LearningGraph Representation Learning
Graph Representation Learning
 
Group and Community Detection in Social Networks
Group and Community Detection in Social NetworksGroup and Community Detection in Social Networks
Group and Community Detection in Social Networks
 
3 Centrality
3 Centrality3 Centrality
3 Centrality
 
Social network analysis
Social network analysisSocial network analysis
Social network analysis
 
Ppt
PptPpt
Ppt
 
03 Ego Network Analysis (2016)
03 Ego Network Analysis (2016)03 Ego Network Analysis (2016)
03 Ego Network Analysis (2016)
 
Data Mining: Graph mining and social network analysis
Data Mining: Graph mining and social network analysisData Mining: Graph mining and social network analysis
Data Mining: Graph mining and social network analysis
 
Social network analysis part ii
Social network analysis part iiSocial network analysis part ii
Social network analysis part ii
 

Viewers also liked

Professor Hendrik Speck - Social and Virtual. - An Analysis Framework for Lar...
Professor Hendrik Speck - Social and Virtual. - An Analysis Framework for Lar...Professor Hendrik Speck - Social and Virtual. - An Analysis Framework for Lar...
Professor Hendrik Speck - Social and Virtual. - An Analysis Framework for Lar...
Hendrik Speck
 
Chromatic graph theory
Chromatic graph theoryChromatic graph theory
Chromatic graph theory
jotasmall
 

Viewers also liked (20)

Introduction to Graph Theory
Introduction to Graph TheoryIntroduction to Graph Theory
Introduction to Graph Theory
 
Network Analysis (SNA/ONA) Methods for Assessment & Measurement
Network Analysis (SNA/ONA) Methods for Assessment & MeasurementNetwork Analysis (SNA/ONA) Methods for Assessment & Measurement
Network Analysis (SNA/ONA) Methods for Assessment & Measurement
 
Sensemaking of social network analysis for the study of learning
Sensemaking of social network analysis for the study of learningSensemaking of social network analysis for the study of learning
Sensemaking of social network analysis for the study of learning
 
Youth Research History
Youth Research HistoryYouth Research History
Youth Research History
 
Reading and writing ones network: Multidiscursive identity practices
Reading and writing ones network: Multidiscursive identity practicesReading and writing ones network: Multidiscursive identity practices
Reading and writing ones network: Multidiscursive identity practices
 
An Introduction to Social Network Analysis and Its Application in Software En...
An Introduction to Social Network Analysis and Its Application in Software En...An Introduction to Social Network Analysis and Its Application in Software En...
An Introduction to Social Network Analysis and Its Application in Software En...
 
Professor Hendrik Speck - Social and Virtual. - An Analysis Framework for Lar...
Professor Hendrik Speck - Social and Virtual. - An Analysis Framework for Lar...Professor Hendrik Speck - Social and Virtual. - An Analysis Framework for Lar...
Professor Hendrik Speck - Social and Virtual. - An Analysis Framework for Lar...
 
An ‘open source’ networked identity - Slides from Youth 2.0
An ‘open source’ networked identity - Slides from Youth 2.0 An ‘open source’ networked identity - Slides from Youth 2.0
An ‘open source’ networked identity - Slides from Youth 2.0
 
Intro to Social Network AnalysisSession
Intro to Social Network  AnalysisSessionIntro to Social Network  AnalysisSession
Intro to Social Network AnalysisSession
 
Class scheduling
Class schedulingClass scheduling
Class scheduling
 
Youth, Identity, and Digital Media
Youth, Identity, and Digital MediaYouth, Identity, and Digital Media
Youth, Identity, and Digital Media
 
Graph coloring Algorithm
Graph coloring AlgorithmGraph coloring Algorithm
Graph coloring Algorithm
 
Application in graph theory
Application in graph theoryApplication in graph theory
Application in graph theory
 
ONA and the tools landscape
ONA and the tools landscapeONA and the tools landscape
ONA and the tools landscape
 
Chromatic graph theory
Chromatic graph theoryChromatic graph theory
Chromatic graph theory
 
Graph
GraphGraph
Graph
 
Organisational Network Analysis
Organisational Network AnalysisOrganisational Network Analysis
Organisational Network Analysis
 
Introduction to Graph and Graph Coloring
Introduction to Graph and Graph Coloring Introduction to Graph and Graph Coloring
Introduction to Graph and Graph Coloring
 
Functional sudoku
Functional sudokuFunctional sudoku
Functional sudoku
 
final presentation of sudoku solver project
final presentation of sudoku solver projectfinal presentation of sudoku solver project
final presentation of sudoku solver project
 

Similar to Introduction to Social Network Analysis

Nm4881 a social network analysis week 6
Nm4881 a social network analysis week 6Nm4881 a social network analysis week 6
Nm4881 a social network analysis week 6
jiahao84
 
Oracal of bacon and social networking analysis final
Oracal of bacon and social networking analysis finalOracal of bacon and social networking analysis final
Oracal of bacon and social networking analysis final
Mia Horrigan
 
Tepl webinar 20032013
Tepl webinar   20032013Tepl webinar   20032013
Tepl webinar 20032013
Nina Pataraia
 
Net Work Shop For Network Creation
Net Work Shop For Network CreationNet Work Shop For Network Creation
Net Work Shop For Network Creation
Patti Anklam
 
Final communication and connectedness v3
Final communication and connectedness v3 Final communication and connectedness v3
Final communication and connectedness v3
Mia Horrigan
 
4.0 social network analysis
4.0 social network analysis4.0 social network analysis
4.0 social network analysis
jilung hsieh
 

Similar to Introduction to Social Network Analysis (20)

Nm4881 a social network analysis week 6
Nm4881 a social network analysis week 6Nm4881 a social network analysis week 6
Nm4881 a social network analysis week 6
 
Internet
InternetInternet
Internet
 
Internet
InternetInternet
Internet
 
Introduction to Computational Social Science
Introduction to Computational Social ScienceIntroduction to Computational Social Science
Introduction to Computational Social Science
 
Oracal of bacon and social networking analysis final
Oracal of bacon and social networking analysis finalOracal of bacon and social networking analysis final
Oracal of bacon and social networking analysis final
 
Ona For Community Roundtable
Ona For Community RoundtableOna For Community Roundtable
Ona For Community Roundtable
 
Social Network Analysis (Part 1)
Social Network Analysis (Part 1)Social Network Analysis (Part 1)
Social Network Analysis (Part 1)
 
A Guide to Social Network Analysis
A Guide to Social Network AnalysisA Guide to Social Network Analysis
A Guide to Social Network Analysis
 
Organization Network Analysis
Organization Network AnalysisOrganization Network Analysis
Organization Network Analysis
 
Tepl webinar 20032013
Tepl webinar   20032013Tepl webinar   20032013
Tepl webinar 20032013
 
Net Work Shop For Network Creation
Net Work Shop For Network CreationNet Work Shop For Network Creation
Net Work Shop For Network Creation
 
Building A High Performance Network That Works Ed Mayuga Amm Communica...
Building A High Performance Network That Works      Ed Mayuga   Amm Communica...Building A High Performance Network That Works      Ed Mayuga   Amm Communica...
Building A High Performance Network That Works Ed Mayuga Amm Communica...
 
Final communication and connectedness v3
Final communication and connectedness v3 Final communication and connectedness v3
Final communication and connectedness v3
 
Psychology of Social Media:Implication for Design
Psychology of Social Media:Implication for DesignPsychology of Social Media:Implication for Design
Psychology of Social Media:Implication for Design
 
Essay Writing Skill
Essay Writing SkillEssay Writing Skill
Essay Writing Skill
 
A proof of concept for automated discourse analysis in support of identificat...
A proof of concept for automated discourse analysis in support of identificat...A proof of concept for automated discourse analysis in support of identificat...
A proof of concept for automated discourse analysis in support of identificat...
 
Beyond Buzz - Web 2.0 Expo - K.Niederhoffer & M.Smith
Beyond Buzz - Web 2.0 Expo - K.Niederhoffer & M.SmithBeyond Buzz - Web 2.0 Expo - K.Niederhoffer & M.Smith
Beyond Buzz - Web 2.0 Expo - K.Niederhoffer & M.Smith
 
Social Network Analysis (SNA) Made Easy
Social Network Analysis (SNA) Made EasySocial Network Analysis (SNA) Made Easy
Social Network Analysis (SNA) Made Easy
 
Wk9 Slides Social Networks - Class.pptx
Wk9 Slides Social Networks - Class.pptxWk9 Slides Social Networks - Class.pptx
Wk9 Slides Social Networks - Class.pptx
 
4.0 social network analysis
4.0 social network analysis4.0 social network analysis
4.0 social network analysis
 

More from Premsankar Chakkingal

More from Premsankar Chakkingal (12)

AI for Educators - Integrating AI in the Classrooms
AI for Educators - Integrating AI in the ClassroomsAI for Educators - Integrating AI in the Classrooms
AI for Educators - Integrating AI in the Classrooms
 
AI in Creative Space
AI in Creative SpaceAI in Creative Space
AI in Creative Space
 
Dynamics of Semantic Networks of Independence Day Speeches
Dynamics of Semantic Networks of Independence Day SpeechesDynamics of Semantic Networks of Independence Day Speeches
Dynamics of Semantic Networks of Independence Day Speeches
 
Introductory Talk on Social Network Analysis at Facebook Developer Circle Me...
Introductory Talk on Social Network Analysis  at Facebook Developer Circle Me...Introductory Talk on Social Network Analysis  at Facebook Developer Circle Me...
Introductory Talk on Social Network Analysis at Facebook Developer Circle Me...
 
Introduction to Agent Based Modeling Using NetLogo
Introduction to Agent Based Modeling Using NetLogoIntroduction to Agent Based Modeling Using NetLogo
Introduction to Agent Based Modeling Using NetLogo
 
Introduction to Technology Assessments As tool for Forecasting and evaluation...
Introduction to Technology Assessments As tool for Forecasting and evaluation...Introduction to Technology Assessments As tool for Forecasting and evaluation...
Introduction to Technology Assessments As tool for Forecasting and evaluation...
 
INTRODUCTION INFORMATION RETRIEVAL EVALUVATION
 INTRODUCTION INFORMATION RETRIEVAL EVALUVATION INTRODUCTION INFORMATION RETRIEVAL EVALUVATION
INTRODUCTION INFORMATION RETRIEVAL EVALUVATION
 
Negotiated Studies - A semantic social network based expert recommender system
Negotiated Studies - A semantic social network based expert recommender systemNegotiated Studies - A semantic social network based expert recommender system
Negotiated Studies - A semantic social network based expert recommender system
 
Business potential of Energy Auditing in Kerala
Business potential of Energy Auditing in KeralaBusiness potential of Energy Auditing in Kerala
Business potential of Energy Auditing in Kerala
 
Negotiated Studies Presentation on Social Network Analysis of Knowledge Networks
Negotiated Studies Presentation on Social Network Analysis of Knowledge NetworksNegotiated Studies Presentation on Social Network Analysis of Knowledge Networks
Negotiated Studies Presentation on Social Network Analysis of Knowledge Networks
 
Hypothesis Testing for Beginners
Hypothesis Testing for BeginnersHypothesis Testing for Beginners
Hypothesis Testing for Beginners
 
Introduction to Genetic Algorithms
Introduction to Genetic AlgorithmsIntroduction to Genetic Algorithms
Introduction to Genetic Algorithms
 

Recently uploaded

Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...
Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...
Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...
panagenda
 
Structuring Teams and Portfolios for Success
Structuring Teams and Portfolios for SuccessStructuring Teams and Portfolios for Success
Structuring Teams and Portfolios for Success
UXDXConf
 

Recently uploaded (20)

WSO2CONMay2024OpenSourceConferenceDebrief.pptx
WSO2CONMay2024OpenSourceConferenceDebrief.pptxWSO2CONMay2024OpenSourceConferenceDebrief.pptx
WSO2CONMay2024OpenSourceConferenceDebrief.pptx
 
Google I/O Extended 2024 Warsaw
Google I/O Extended 2024 WarsawGoogle I/O Extended 2024 Warsaw
Google I/O Extended 2024 Warsaw
 
ECS 2024 Teams Premium - Pretty Secure
ECS 2024   Teams Premium - Pretty SecureECS 2024   Teams Premium - Pretty Secure
ECS 2024 Teams Premium - Pretty Secure
 
Optimizing NoSQL Performance Through Observability
Optimizing NoSQL Performance Through ObservabilityOptimizing NoSQL Performance Through Observability
Optimizing NoSQL Performance Through Observability
 
Simplified FDO Manufacturing Flow with TPMs _ Liam at Infineon.pdf
Simplified FDO Manufacturing Flow with TPMs _ Liam at Infineon.pdfSimplified FDO Manufacturing Flow with TPMs _ Liam at Infineon.pdf
Simplified FDO Manufacturing Flow with TPMs _ Liam at Infineon.pdf
 
Syngulon - Selection technology May 2024.pdf
Syngulon - Selection technology May 2024.pdfSyngulon - Selection technology May 2024.pdf
Syngulon - Selection technology May 2024.pdf
 
Extensible Python: Robustness through Addition - PyCon 2024
Extensible Python: Robustness through Addition - PyCon 2024Extensible Python: Robustness through Addition - PyCon 2024
Extensible Python: Robustness through Addition - PyCon 2024
 
Overview of Hyperledger Foundation
Overview of Hyperledger FoundationOverview of Hyperledger Foundation
Overview of Hyperledger Foundation
 
Portal Kombat : extension du réseau de propagande russe
Portal Kombat : extension du réseau de propagande russePortal Kombat : extension du réseau de propagande russe
Portal Kombat : extension du réseau de propagande russe
 
TopCryptoSupers 12thReport OrionX May2024
TopCryptoSupers 12thReport OrionX May2024TopCryptoSupers 12thReport OrionX May2024
TopCryptoSupers 12thReport OrionX May2024
 
Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...
Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...
Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...
 
The Metaverse: Are We There Yet?
The  Metaverse:    Are   We  There  Yet?The  Metaverse:    Are   We  There  Yet?
The Metaverse: Are We There Yet?
 
Secure Zero Touch enabled Edge compute with Dell NativeEdge via FDO _ Brad at...
Secure Zero Touch enabled Edge compute with Dell NativeEdge via FDO _ Brad at...Secure Zero Touch enabled Edge compute with Dell NativeEdge via FDO _ Brad at...
Secure Zero Touch enabled Edge compute with Dell NativeEdge via FDO _ Brad at...
 
Using IESVE for Room Loads Analysis - UK & Ireland
Using IESVE for Room Loads Analysis - UK & IrelandUsing IESVE for Room Loads Analysis - UK & Ireland
Using IESVE for Room Loads Analysis - UK & Ireland
 
Structuring Teams and Portfolios for Success
Structuring Teams and Portfolios for SuccessStructuring Teams and Portfolios for Success
Structuring Teams and Portfolios for Success
 
Salesforce Adoption – Metrics, Methods, and Motivation, Antone Kom
Salesforce Adoption – Metrics, Methods, and Motivation, Antone KomSalesforce Adoption – Metrics, Methods, and Motivation, Antone Kom
Salesforce Adoption – Metrics, Methods, and Motivation, Antone Kom
 
IESVE for Early Stage Design and Planning
IESVE for Early Stage Design and PlanningIESVE for Early Stage Design and Planning
IESVE for Early Stage Design and Planning
 
Easier, Faster, and More Powerful – Notes Document Properties Reimagined
Easier, Faster, and More Powerful – Notes Document Properties ReimaginedEasier, Faster, and More Powerful – Notes Document Properties Reimagined
Easier, Faster, and More Powerful – Notes Document Properties Reimagined
 
Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...
Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...
Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...
 
Where to Learn More About FDO _ Richard at FIDO Alliance.pdf
Where to Learn More About FDO _ Richard at FIDO Alliance.pdfWhere to Learn More About FDO _ Richard at FIDO Alliance.pdf
Where to Learn More About FDO _ Richard at FIDO Alliance.pdf
 

Introduction to Social Network Analysis

  • 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 7
  • 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 8
  • 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. 16
  • 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 17 Source: http://www.orgnet.com/sna.html
  • 18. What’s the Moral of the Story? 18
  • 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 24

Editor's Notes

  1. Insert a map of your country.
  2. Insert a picture illustrating a season in your country.
  3. Insert a picture illustrating a custom or tradition here.
  4. Check on the poll at this point…
  5. Insert a picture of an animal and or plant found in your country.
  6. Morale of the Story: Network Usefulness Depends on the Quality of the Relationships