Proposals for Social Network Analysis of Big Data

Given the emergence of big data generated by massive digitization, as well as the growing access to information from the so-called second digital revolution, sociologists face a number of methodological challenges to better understand social life: data collection, new ways of sampling, automatic coding and statistical analysis of information. 

This presentation proposes the analysis of information based on data binarization. The idea is to build three-dimensional binary matrices formed by 1) temporal or spatial sets, 2) scenarios and 3) events or characteristics, supported by matrices with their attributes. The treatment of this structure is based on the methodology of two-mode networks, combined with statistical tools for selection and location of nodes, and representation of edges. 

The proposed analysis, which runs in the cloud, will be explained using a variety of examples that range from the analysis of photo collections, content analysis of text, representation of concerts and exhibitions, surveys of personal correspondence, … to the analysis of multiple response questions in questionnaires.