Introduction to social network analysis
Social network analysis (SNA) can be used to analyse patterns of information and knowledge flow, enabling the identification of individuals playing important structural roles within a network, such as bottlenecks and boundary spanners, as well as subgroups such as cliques.
- Louise Cooke's session at DREaM event 2 on 25 October gave a useful introduction to SNA theory. The session page includes slides and video (embedded below), as well as a summary:
- The bulk of the livetweeting action can be found in the session summary, but there is surely room for something a little gratuitous:
- Collecting the data
- The good news is that SNA is not all about maths or noodling with Google spreadsheets - data collection is only the first stage. An analysis of workshop participants was undertaken as part of the session, which it is planned to repeat at the end of the project to help assess impact.
- Interpreting the results
- Initial findings from the workshop exercise were that the network was fairly well connected, with 20 cliques/clusters. The acquaintanceship network was slightly more connected than the knowledge and expertise network:
- A couple of further examples:
- The truly awesome work by @mhawksey now slots into place - time to give the googledocery another go to get closer to the interesting stuff:
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