Stochastic Blockmodeling for the Analysis of Big Data

The aim of this paper is to consider the stochastic blockmodel to obtain clusters of units as regards patterns of similar relations; moreover we want to analyze the relations between clusters. Blockmodeling is a technique usually applied in social network analysis focusing on the relations between “actors” i.e. units. In our time people and devices constantly generate data. The network is generating location and other data that keeps services running and ready to use in every moment. This rapid development in the availability and access to data has induced the need for better analysis techniques to understand the various phenomena. Blockmodeling techniques and Clustering algorithms, can be used for this aim. In this paper application regards the Web.