Symbolic Data Analysis of Large Scale Spatial Network Data
Carlo Drago1,* , Alessandra Reale1
1. University of Rome “Niccolò Cusano” and Italian National Institute of Statistics (ISTAT)
*Contact author: c.drago@mclink.it
Keywords: Symbolic Data Analysis, Social Network Analysis, Community Detection, Spatial Data
Mining
Modern spatial networks are ubiquitous in various different contexts and are increasingly massive on
their size. The challenges for large-scale spatial networks call for new methodologies and approaches
which can allow to extract the relevant patterns on data. In this work we will examine spatial networks
data, taking into account their characteristics, and we will consider different approaches in order to
represent and analyze these networks by means of Symbolic Data. From the representations of the
networks, we will show different Symbolic Data Analysis approaches to detect the different patterns is
possible to find on data. We will conduct a simulation study and an application on real data.
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