As early as in 2009, Gartner predicted that Social Network Analysis (SNA) could be an important tool for detecting business patterns or disruptions and a source of new unprecedented insights for organisations. Today, SNA-based tools, as components of advanced analytic platforms (including predictive platforms), become indispensable for defining long-term strategies and managing daily operations.
The key feature of SNA is its unique perspective; instead of examining the properties of subjects (e.g. their attributes, attitudes, behaviours etc.) it focuses on the links between them. In this case, networks of links between different items (called “nodes”) are analysed.
In general, it is assumed that SNA allows for analysing a network on three basic levels:
- Overall network level(e.g. number of connections (“density”); distance between network components; etc.);
- Network part level(e.g. definition of relationships between different groups; identification of central and isolated groups; identification of the width of links between groups; etc.);
- Network node level(e.g. identification of network integrators, key intermediaries, peripheral subjects, etc.).
SAS® Visual Investigator has the functionality of data mining and exploration of documents from different sources and visualising them in an SNA network. With this functionality, it is possible to uncover hidden connections and interdependencies, aggregate the appropriately interpreted sets into groups and share the results with others to run more in-depth analyses and prepare more detailed reports.
More information about SAS® Visual Investigator is available here.