Mining urban lifestyles: urban computing, human behavior and recommender systems

This is the author accepted manuscript. The final version is available from IET via the DOI in this recordIn the last decade, the digital age has sharply redefined the way we study human behavior. With the advancement of data storage and sensing technologies, electronic records now encompass a diverse spectrum of human activity, ranging from location data, phone, and email communication to Twitter activity and opensource contributions on Wikipedia and OpenStreetMap. In particular, the study of the shopping and mobility patterns of individual consumers has the potential to give deeper insight into the lifestyles and infrastructure of the region. Credit card records (CCRs) provide detailed insight into purchase behavior and have been found to have inherent regularity in consumer shopping patterns; call detail records (CDRs) present new opportunities to understand human mobility, analyze wealth, and model social network dynamics

Epidemics of liquidity shortages in interbank markets

This is the author accepted manuscript. the final version is avilable from Elsevier via the DOI in this recordFinancial contagion from liquidity shocks has being recently ascribed as a prominent driver of systemic risk in interbank lending markets. Building on standard compartment models used in epidemics, in this work we develop an EDB (Exposed–Distressed–Bankrupted) model for the dynamics of liquidity shocks reverberation between banks, and validate it on electronic market for interbank deposits data. We show that the interbank network was highly susceptible to liquidity contagion at the beginning of the 2007/2008 global financial crisis, and that the subsequent micro-prudential and liquidity hoarding policies adopted by banks increased the network resilience to systemic risk—yet with the undesired side effect of drying out liquidity from the market. We finally show that the individual riskiness of a bank is better captured by its network centrality than by its participation to the market, along with the currently debated concept of “too interconnected to fail”.European Union FP7European Union Horizon 202

The Italian primary school-size distribution and the city-size: A complex nexus

This is the final version. Available from Nature Research via the DOI in this record.We characterize the statistical law according to which Italian primary school-size distributes. We find that the school-size can be approximated by a log-normal distribution, with a fat lower tail that collects a large number of very small schools. The upper tail of the school-size distribution decreases exponentially and the growth rates are distributed with a Laplace PDF. These distributions are similar to those observed for firms and are consistent with a Bose-Einstein preferential attachment process. The body of the distribution features a bimodal shape suggesting some source of heterogeneity in the school organization that we uncover by an in-depth analysis of the relation between schools-size and city-size. We propose a novel cluster methodology and a new spatial interaction approach among schools which outline the variety of policies implemented in Italy. Different regional policies are also discussed shedding lights on the relation between policy and geographical features

Reconstructing Mesoscale Network Structures

When facing the problem of reconstructing complex mesoscale network structures, it is generally believed that models encoding the nodes organization into modules must be employed. The present paper focuses on two block structures that characterize the empirical mesoscale organization of many real-world networks, i.e., the bow-tie and the core-periphery ones, with the aim of quantifying the minimal amount of topological information that needs to be enforced in order to reproduce the topological details of the former. Our analysis shows that constraining the network degree sequences is often enough to reproduce such structures, as confirmed by model selection criteria as AIC or BIC. As a byproduct, our paper enriches the toolbox for the analysis of bipartite networks, still far from being complete: both the bow-tie and the core-periphery structure, in fact, partition the networks into asymmetric blocks characterized by binary, directed connections, thus calling for the extension of a recently proposed method to randomize undirected, bipartite networks to the directed case

Randomizing bipartite networks: The case of the World Trade Web

This is the final version. Available from Nature Research via the DOI in this record. Within the last fifteen years, network theory has been successfully applied both to natural sciences and to socioeconomic disciplines. In particular, bipartite networks have been recognized to provide a particularly insightful representation of many systems, ranging from mutualistic networks in ecology to trade networks in economy, whence the need of a pattern detection-oriented analysis in order to identify statistically-significant structural properties. Such an analysis rests upon the definition of suitable null models, i.e. upon the choice of the portion of network structure to be preserved while randomizing everything else. However, quite surprisingly, little work has been done so far to define null models for real bipartite networks. The aim of the present work is to fill this gap, extending a recently-proposed method to randomize monopartite networks to bipartite networks. While the proposed formalism is perfectly general, we apply our method to the binary, undirected, bipartite representation of the World Trade Web, comparing the observed values of a number of structural quantities of interest with the expected ones, calculated via our randomization procedure. Interestingly, the behavior of the World Trade Web in this new representation is strongly different from the monopartite analogue, showing highly non-trivial patterns of self-organization.GROWTHCO

Complex delay dynamics on railway networks from universal laws to realistic modelling

This is the final version. Available from EDP Sciences via the DOI in this record.The datasets supporting the conclusions of this article are included within the article (and its additional files).Railways are a key infrastructure for any modern country. The reliability and resilience of this peculiar transportation system may be challenged by different shocks such as disruptions, strikes and adverse weather conditions. These events compromise the correct functioning of the system and trigger the spreading of delays into the railway network on a daily basis. Despite their importance, a general theoretical understanding of the underlying causes of these disruptions is still lacking. In this work, we analyse the Italian and German railway networks by leveraging on the train schedules and actual delay data retrieved during the year 2015. We use these data to infer simple statistical laws ruling the emergence of localized delays in different areas of the network and we model the spreading of these delays throughout the network by exploiting a framework inspired by epidemic spreading models. Our model offers a fast and easy tool for the preliminary assessment of the effectiveness of traffic handling policies, and of the railway network criticalities.John Templeton FoundationAustrian Research Promotion Agency FFGNewton International FellowshipThe Royal SocietyThe British AcademyAcademy of Medical Science

From innovation to diversification: A simple competitive model

This is the final version. Avaialable from Public Library of Science via the DOI in this record.The raw data about export flows has been purchased from CEPII (http://www.cepii.fr/CEPII/en/bdd_modele/presentation.asp?id=1), see BACI dataset. However, the use of this dataset is not exclusive and anyone can purchase it. A free version for academic and research institutions is available on the United Nations COMTRADE website (http://comtrade.un.org/), see the Trade Dataset.3 Dec 2015: The PLOS ONE Staff (2015) Correction: From Innovation to Diversification: A Simple Competitive Model. PLOS ONE 10(12): e0144564. https://doi.org/10.1371/journal.pone.0144564Few attempts have been proposed in order to describe the statistical features and historical evolution of the export bipartite matrix countries/products. An important standpoint is the introduction of a products network, namely a hierarchical forest of products that models the formation and the evolution of commodities. In the present article, we propose a simple dynamical model where countries compete with each other to acquire the ability to produce and export new products. Countries will have two possibilities to expand their export: innovating, i.e. introducing new goods, namely new nodes in the product networks, or copying the productive process of others, i.e. occupying a node already present in the same network. In this way, the topology of the products network and the country-product matrix evolve simultaneously, driven by the countries push toward innovation.Growthcom Project FP7Crisis La

Big data fusion to estimate urban fuel consumption: A case study of Riyadh

This is the author accepted manuscript. The final version is available from SAGE Publications via the DOI in this recordFalling oil revenues and rapid urbanization are putting a strain on the budgets of oil-producing nations, which often subsidize domestic fuel consumption. A direct way to decrease the impact of subsidies is to reduce fuel consumption by reducing congestion and car trips. As fuel consumption models have started to incorporate data sources from ubiquitous sensing devices, the opportunity is to develop comprehensive models at urban scale leveraging sources such as Global Positioning System (GPS) data and Call Detail Records. This paper combines these big data sets in a novel method to model fuel consumption within a city and estimate how it may change in different scenarios. To do so a fuel consumption model was calibrated for use on any car fleet fuel economy distribution and applied in Riyadh, Saudi Arabia. The model proposed, based on speed profiles, was then used to test the effects on fuel consumption of reducing flow, both randomly and by targeting the most fuelinefficient trips in the city. The estimates considerably improve baseline methods based on average speeds, showing the benefits of the information added by the GPS data fusion. The presented method can be adapted to also measure emissions. The results constitute a clear application of data analysis tools to help decision makers compare policies aimed at achieving economic and environmental goals.MIT Energy Solutions InitiativeCenter for Complex Engineering Systems, King Abdulaziz City for Science and TechnologyRoyal SocietyBritish AcademyAcademy of Medical Science

Detecting early signs of the 2007-2008 crisis in the world trade

This is the final version. Available from Nature Research via the DOI in this record. Since 2007, several contributions have tried to identify early-warning signals of the financial crisis. However, the vast majority of analyses has focused on financial systems and little theoretical work has been done on the economic counterpart. In the present paper we fill this gap and employ the theoretical tools of network theory to shed light on the response of world trade to the financial crisis of 2007 and the economic recession of 2008-2009. We have explored the evolution of the bipartite World Trade Web (WTW) across the years 1995-2010, monitoring the behavior of the system both before and after 2007. Our analysis shows early structural changes in the WTW topology: since 2003, the WTW becomes increasingly compatible with the picture of a network where correlations between countries and products are progressively lost. Moreover, the WTW structural modification can be considered as concluded in 2010, after a seemingly stationary phase of three years. We have also refined our analysis by considering specific subsets of countries and products: the most statistically significant early-warning signals are provided by the most volatile macrosectors, especially when measured on developing countries, suggesting the emerging economies as being the most sensitive ones to the global economic cycles.GROWTHCOMSIMPO