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. References Billard, L., & Diday, E. (2003). From the statistics of data to the statistics of knowledge: symbolic data analysis. Journal of the American Statistical Association, 98(462), 470-487. Diday, E., & Noirhomme-Fraiture, M. (Eds.). (2008). Symbolic data analysis and the SODAS software. J. Wiley & Sons. Drago C. (2015) Large Network Analysis: Representing the Community Structure by Means of Interval Data. Fifth International Workshop on Social Network Analysis (ARS 2015); 04/2015 Giordano G., Brito M. P. , (2014) Social Networks as Symbolic Data, in: Analysis and Modeling of Complex Data in Behavioral and Social Sciences, Edited by Vicari, D, Okada, A, Ragozini, G, Weihs, C. (Eds, 06/2014; Springer Series: Studies in Classification, Data Analysis, and Knowledge Organization., ISBN: 978-3-319-06691-2 Giordano G., Signoriello S. and Vitale M.P. (2008) Comparing Social Networks in the framework of Complex Data Analysis. CLEUP Editore, Padova: pp.1- 2, In: XLIV Riunione Scientifica della Società Italiana di Statistica