Eur. Phys. J. B (2015) 88: 194
https://doi.org/10.1140/epjb/e2015-60357-1

Regular Article

Statistical analysis of Nomao customer votes for spots of France

¹ Informatics Laboratory, Institute for Computer Science and Control, Hungarian Academy of Sciences (MTA SZTAKI), Pf. 63, 1518 Budapest, Hungary
² Technical University Budapest, 1111 Budapest, Hungary
³ Eötvös University Budapest, 1053 Budapest, Hungary
⁴ Departamento de Física Teórica, GIyA, CNEA, Av. Libertador 8250, C1429 BNP Buenos Aires, Argentina
⁵ Nomao.com, 1 av Jean Rieux, 31500 Toulouse, France
⁶ LPS, Université Paris-Sud, CNRS, UMR 8502, 91405, Orsay, France
⁷ Laboratoire de Physique Théorique du CNRS, IRSAMC, Université de Toulouse, UPS, 31062 Toulouse, France

^a e-mail: dima@irsamc.ups-tlse.fr

Received: 5 May 2015
Published online: 3 August 2015

Abstract

We investigate the statistical properties of votes of customers for spots of France collected by the startup company Nomao. The frequencies of votes per spot and per customer are characterized by a power law distribution which remains stable on a time scale of a decade when the number of votes is varied by almost two orders of magnitude. Using the computer science methods we explore the spectrum and the eigenvalues of a matrix containing user ratings to geolocalized items. Eigenvalues nicely map to large towns and regions but show certain level of instability as we modify the interpretation of the underlying matrix. We evaluate imputation strategies that provide improved prediction performance by reaching geographically smooth eigenvectors. We point on possible links between distribution of votes and the phenomenon of self-organized criticality.