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Introduction to Social Network Analysis

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Social network analysis [SNA] is the mapping and measuring of relationships and flows between people, groups, organizations, computers, URLs, and other connected information/knowledge entities. SNA provides both a visual and a mathematical analysis of human relationships.

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Introduction to Social Network Analysis

  1. 1. SOCIAL NETWORK ANALYSIS PREM SANKAR C DEPT OF FUTURES STUDIES KERALA UNIVERSITY
  2. 2. “Think Link” “Social relationships are hidden to Real World”
  3. 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. 4. Actors (Nodes/ Vertices)  Actors –are the smallest unit of a network  Persons  Organizations  Countries  Companies  Animals  Words  Web pages  Families
  5. 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. 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. 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. 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. 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. 10. PRACTICAL APPLICATIONS OF SNA... helping you see your interconnected world
  11. 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. 12. SNA for Sports all about connections from people to people
  13. 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. 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. 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. 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. 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. 18. What’s the Moral of the Story? 18
  19. 19. Political blogs
  20. 20. Organizations
  21. 21. Facebook networks
  22. 22. Ingredient networks
  23. 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

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