DREaM Event 2: Louise Cooke
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Slides to accompany Dr Louise Cooke's workshop session "An introduction to social network analysis" presented at DREaM Event 2. For more information about the event, please visit http://lisresearch.org/dream-project/dream-event-2-workshop-tuesday-25-october-2011/
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DREaM Event 2: Louise Cooke
- 1. An Introduction to Social Network Analysis DREaM Workshop October 2011 Louise Cooke Senior Lecturer
- 7. For example…
- 9. An example of a network diagram
- 10. Knowledge Exchange among EU Countries Source: www. Orgnet.com Based on data from 2003-4.
- 23. A Practical Example: Research Networks - by University (1)
- 24. Research Networks – by University (2)
- 31. Any Questions?
Notas del editor
- Introduce terms nodes, actors, dyadic, ties. Also, discuss directional and valued ties.
- Note that the term ‘social’ is used in its broadest conception to imply a relationship – it does not necessarily imply a relationship of a ‘social’ kind. SNA does not just apply to the analysis of social networking sites! Based on mathematical graph theory.
- Sets of nodes, linked by ties. Mention also the Katrina ‘blame game’.
- Connectors = Germany and Finland. Mavens = Slovenia, Finland, then Russia. (Where people go to in network for knowledge).
- Six degrees of Kevin Bacon – any film actor can be linked by no more than 6 ties to Kevin Bacon. Small world phenomenon of 6 degrees of separation – everyone is an average of 6 “steps” away from each person on earth.
- Euler – Swiss mathematician and physicist, made significant developments in graph theory and mathematical notation. Hawthorne studies – bank wiring room experiments revealed existence of informal groups or ‘cliques’ within formal groups. Workers were more responsive to peer pressure of social group than incentives offered by management. Hence it is in organisations’ interest to collaborate with informal groups. 429 papers published 2010-11. What happened in mid-1990s? Take-up of W3 with introduction of Mosaic browser in 1993.
- Strength of weak ties – Granovetter Embeddedness – work related transactions tend to overlap with patterns of social relations (Granovetter, 1985). Business is embedded in social networks: knowledge transfer networks tend to emulate social networks. Social capital – lack of connectedness can impact negatively on business success.
- We are taking the concepts of nodes, ties (also called arcs and edges) and dyads as already understood. Component = subset of graph where there is a path between each other. Total connectivity = all nodes in network are one component. Density = indicator of general level of connectedness. If every node is directly connected to every other = complete graph. Degree centrality of a node = no. of ties to node. Closeness centrality of a node = total distance of this node from all other nodes. Betweenness centrality = number of times a node needs a given node to reach another node. Cliques – subgraph in which any node is directly connedted to any other node of the subgraph.