The use of Multidimensional Data Analysis in the framework of Social Network Analysis in order to explore roles and positions of actors in a network will be addressed. Emphasis will be put on data handling and visualization. Firstly, the use of Contiguity Analysis able to deal with relational data will allow defining data analysis able to synthesize and visualize the patterns of social relationships in a metric space. Then, since interactions are often derived from the presence of actors at events or activities (two-mode network data), in addition to the relational data, the availability of external information gathered on both actors and events will be considered. To explore the effect of external information about ties, we show how to decompose the original network data matrix and representing external information with a suitable matrix coding. This allows obtaining peculiar relational data matrices that include the effects of such new information. The derived adjacency matrices can then be analyzed from the network analysis perspective. In particular, we look for groups of structurally equivalent actors obtained through clustering methods. Illustrative examples in the framework of scientific collaboration and Marketing will give a major insight into the proposed strategy.
|Titolo:||Exploratory data analysis and contiguity relations: An outlook|
|Data di pubblicazione:||2015|
|Appare nelle tipologie:||4.2 Abstract|