Personal networks (tutorial)

From visone manual
Revision as of 08:17, 5 June 2012 by Lerner (talk | contribs)
Jump to navigation Jump to search

EgoNet is a software to conduct interviews in which the personal networks of respondents are collected. This tutorial explains (1) how to load data collected with EgoNet into visone and (2) how to cluster, aggregate, and visualize collections of personal networks using the methodology proposed in: Ulrik Brandes, Juergen Lerner, Miranda J. Lubbers, Chris McCarty, and Jose Luis Molina "Visual Statistics for Collections of Clustered Graphs". Proc. IEEE Pacific Visualization Symp. (PacificVis'08), 2008 (link to pdf).

The data we are going to use for illustration in this tutorial have been collected within a study analyzing personal networks of immigrants in Barcelona. To follow the steps outlined in this tutorial you should download the Signos data and extract (unzip) this file on your computer. Furthermore you need the EgoNet2GraphML software to convert EgoNet interviews to GraphML files and apply the clustering and aggregation.

Converting EgoNet interviews into GraphML files

Visual analysis of personal networks on the individual level

Class-level analysis of personal networks

Defining a network partition based on node attributes

Definition of intra-class and inter-class tie weights

Visual analysis of individual personal networks on the class level

Tendency and dispersion in collections of personal networks