Zbigniew Smoreda

• Ph.D.
• Senior Researcher at Orange Labs, Paris, France

Réseaux and changing sociability Réseaux was created under the auspices of the Centre National d’Études des Télécommunications (CNET) to bring closer together media communication research and the interpersonal exchanges that take place with telecommunication tools. This synthesis explores the journal’s production both on the question of telephone c...

While the size of cities is known to play a fundamental role in social and economic life, its impact on the structure of the underlying social networks is not well understood. Here, by mapping society-wide communication networks to the urban areas of two European countries, we show that both the number of social contacts and the total communication...

Large-scale networks of human interaction, in particular country-wide telephone call networks, can be used to redraw geographical maps by applying algorithms of topological community detection. The geographic projections of the emerging areas in a few recent studies on single regions have been suggested to share two distinct properties: first, they...

In this paper, we analyze statistical properties of a communication network constructed from the records of a mobile phone company. The network consists of 2.5 million customers that have placed 810 million communications (phone calls and text messages) over a period of 6 months and for whom we have geographical home localization information. It is...

Communication mediated by various technologies (from ordinary mail to today's Information and Communication Technologies (ICT)) provides important evidence for the study of social networks. Given that networks generate the possibility of interpersonal communication, data on technology use can provide important information on sociability. However, i...

Amid recent studies that have been exploring the wide impact that COVID-19 containment policies have had across sectors and industries, we investigate how mobility restrictions enacted in French cities during the later stages of the pandemic have affected the usage of smartphones and mobile applications. Leveraging a large-scale dataset of over 14...

Network Signalling Data (NSD) have the potential to provide continuous spatio-temporal information about the presence, mobility, and usage patterns of cell phone services by individuals. Such information is invaluable for monitoring large urban areas and supporting the implementation of decision-making services. When analyzed in real time, NSD can...

Network Signalling Data (NSD) have the potential to provide continuous spatio-temporal information about the presence, mobility, and usage patterns of cell phone services by individuals. Such information is invaluable for monitoring large urban areas and supporting the implementation of decision-making services. When analyzed in real time, NSD can...

The widespread availability of inexpensive mobile broadband has democratized access to digital services in developed countries. While this has supposedly closed digital divides among the population, more subtle inequalities may still be present that are not driven by the accessibility to mobile services, rather by the heterogeneous capability of in...

Explainable artificial intelligence (XAI) provides explanations for not interpretable machine learning (ML) models. While many technical approaches exist, there is a lack of validation of these techniques on real-world datasets. In this work, we present a use-case of XAI: an ML model which is trained to estimate electrification rates based on mobil...

Digital sources have been enabling unprecedented data-driven and large-scale investigations across a wide range of domains, including demography, sociology, geography, urbanism, criminology, and engineering. A major barrier to innovation is represented by the limited availability of dependable digital datasets, especially in the context of data gat...

Explainable artificial intelligence (XAI) provides explanations for not interpretable machine learning (ML) models. While many technical approaches exist, there is a lack of validation of these techniques on real-world datasets. In this work, we present a use-case of XAI: an ML model which is trained to estimate electrification rates based on mobil...

Temporary migration trips are circulatory journeys that can be associated with tourism as these trips aren’t made on a regular basis. They’re often left unmeasured due to limited data sources, and thereby missing from regional and national travel demand models. This article presents a methodology for inferring large-scale temporary migration trips...

Reliable and timely information on socio-economic status and divides is critical to social and economic research and policing. Novel data sources from mobile communication platforms have enabled new cost-effective approaches and models to investigate social disparity, but their lack of interpretability, accuracy or scale has limited their relevance...

Reliable and affordable access to electricity has become one of the basic needs for humans and is, as such, at the top of the development agenda. It contributes to socio-economic development by transforming the whole spectrum of people’s lives—food, education, healthcare. It spurs new economic opportunities, thus improving livelihoods. Using a comp...

Call detail records (CDR) collected by mobile phone network providers have been largely used to model and analyze human-centric mobility. Despite their potential, they are limited in terms of both spatial and temporal accuracy thus being unable to capture detailed human mobility information. Network Signaling Data (NSD) represent a much richer sour...

Spatiotemporal data, and more specifically origin-destination matrices, are critical inputs to mobility studies for transportation planning and urban management purposes. Traditionally, high-cost and hard-to-update household travel surveys are used to produce origin-destination flow information of individuals’ whereabouts. In this paper, we propose...

This paper proposes a framework to extract dynamic trip flows and travel demand patterns from large-scale 2 G and 3 G cellular signaling data. Novel data pre-processing techniques based on cell phone activity metrics are presented. The trip extraction method relies on the detection of stationary activities to form trip sequences related to resident...

In this chapter, the authors develop one such quality assessment for home detection methods from call detailed record (CDR) data. They argue that little research exists on the validity and related errors of home detection methods and that the sensitivity of results to researcher choices when setting up home detection algorithms (HDAs) is poorly und...

High quality census data are not always available in developing countries. Instead, mobile phone data are becoming a popular proxy to evaluate the density, activity and social characteristics of a population. They offer additional advantages: they are updated in real-time, include mobility information and record visitors’ activity. However, we show...

A reliable and affordable access to electricity has become one of the basic needs for humans and is, as such, at the top of the development agenda. It contributes to socio-economic development by transforming the whole spectrum of people's lives - food, education, health care; it spurs new economic opportunities and thus improves livelihoods. Using...

For billing purposes, telecom operators collect communication logs of our mobile phone usage activities. These communication logs or so called CDR has emerged as a valuable data source for human behavioral studies. This work builds on the transportation modeling literature by introducing a new approach of crowdsource-based route choice behavior dat...

Origin-Destination (O-D) matrices are a necessary input for transport planning to support both mobility modeling and analysis tasks. Several research works have investigated the possibility to compute O-D matrices from mobile phone data. However, most of these works rely on billing data (call detail records). In this paper, network signaling data i...

Les matrices origines-destinations (O-D) sont nécessaires à la planification des transports que ce soit pour alimenter les travaux de modélisation ou l’analyse de la mobilité. De nombreux travaux ont été réalisés sur la production de matrices à partir des données de la téléphonie mobile. La plupart des travaux porte sur les données de facturation....

Estimating migration flows and forecasting future trends is important, both to understand the causes and effects of migration and to implement policies directed at supplying particular services. Over the years, less research has been done on modeling migration flows than the efforts allocated to modeling other flow types, for instance, commute. Lim...

Call Detail Records provide information on the origin and destination of voice calls at the level of the base stations in a cellular network. The low spatial resolution and sparsity of these data constitutes challenges in using them for mobility characterization. In this paper we analyze the impact on the detection of commuting patterns of four par...

High quality census data are not always available in developing countries. Instead, mobile phone data are becoming a go to proxy to evaluate population density, activity and social characteristics. They offer additional advantages for infrastructure planning such as being updated in real-time, including mobility information and recording temporary...

Spatiotemporal data, and more specifically origin-destination matrices, are critical inputs to mobility studies for transportation planning and urban management purposes. In this paper, we propose a methodology to infer origin-destination (O-D) matrices based on passively-collected cellular signaling data of millions of anonymized mobile phone user...

The breadcrumbs we leave behind when using our mobile phones—who somebody calls, for how long, and from where—contain unprecedented insights about us and our societies. Researchers have compared the recent availability of large-scale behavioral datasets, such as the ones generated by mobile phones, to the invention of the microscope, giving rise to...

Mobile phone data are an interesting new data source for official statistics. However, multiple problems and uncertainties need to be solved before these data can inform, support or even become an integral part of statistical production processes. In this article, we focus on arguably the most important problem hindering the application of mobile p...

Commuting is recurring travel between home and workplace, which accounts for most trips made daily. Understanding commuting patterns and flows is therefore essential for city and transport system design and planning. Traditionally, commuting flow information was collected using surveys and interviews, which are expensive and time-consuming. This pa...

Large-scale location based traces, such as mobile phone data, have been identified as a promising data source to complement or even enrich official statistics. In many cases, a prerequisite step to deploy the massively gathered data is the detection of home location from individual users. The problem is that little research exists on the validation...

In this contribution we summarize insights on the geographical veracity of using mobile phone data to create (statistical) indicators. We focus on problems that persist with spatial allocation, spatial delineation and spatial aggregation of information obtained from mobile phone data. For each of the cases, we offer insights from our works on a Fre...

Mobile phone data are an interesting new data source for official statistics. However, multiple problems and uncertainties need to be solved before these data can inform, support or even become an integral part of statistical production processes. In this paper, we focus on arguably the most important problem hindering the application of mobile pho...

Non-continuous location traces inferred from Call Detail Records (CDR) at population scale are increasingly becoming available for research and show great potential for automated detection of meaningful places. Yet, a majority of Home Detection Algorithms (HDAs) suffer from "blind" deployment of criteria to define homes and from limited possibiliti...

In this paper, we propose a correction of the Mobility Entropy indicator (ME) used to describe the diversity of individual movement patterns as can be captured by data from mobile phones. We argue that a correction is necessary because standard calculations of ME show a structural dependency on the geographical density of observation points, render...

Analyzing long-distance travel demand has become increasingly relevant because the share of traffic induced by journeys related to remote activities which are not part of daily life is growing. In today’s mobile world, such journeys are responsible for almost 50 percent of all traffic. Traditionally, surveys have been used to gather data needed to...

Mobile phone operators produce enormous amounts of data. In this paper we present applications performed with a dataset (probe data) collected by the operator Orange in 2017 in Rhône Alpes Region, France. Trips are deduced from the spatio-temporal trajectory of devices through a hypothesis of stationarity in order to define activities. Trips are th...

In this work, we discuss how an existing algorithm to extract long-distance trips from mobile phone data (Janzen et al., 2016 a,b) can be supplemented with man-made heuristics to arrive at plausible domestic tourism trips. In total, we detect 18,380 domestic tourism trips from mobile phone data of 69,000 users sampled in 32 cities in France. By ana...

We investigate how individual mobile services are consumed at a national scale, by studying data collected in a 3G/4G mobile network deployed over a major European country. Through correlation and clustering analyses, our study unveils a strong heterogeneity in the demand for different mobile services, both in time and space. In particular, we show...

L’article porte sur le potentiel des données passives de la téléphonie mobile pour produire des matrices origine-destination de déplacements. L’utilisation des données Orange (contenant appels, SMS ainsi que les données de signalisation) collectées du 31 mars au 11 avril 2009 en Île-de-France permet grâce aux estampilles spatiotemporelles, de const...

A longitudinal mobile phone data that include both location and communication logs is analyzed to infer social influence in terms of ego-network effect in the commute mode choice. The results show that person’s strong ties are more important to determine if driving is the person’s transport mode choice, whereas weak ties are more important to deter...

Epidemic outbreaks are an important healthcare challenge, especially in developing countries where they represent one of the major causes of mortality. Approaches that can rapidly target subpopulations for surveillance and control are critical for enhancing containment processes during epidemics. Using a real-world dataset from Ivory Coast, this wo...

Epidemic outbreaks are an important healthcare challenge, especially in developing countries where they represent one of the major causes of mortality. Approaches that can rapidly target subpopulations for surveillance and control are critical for enhancing containment processes during epidemics. Using a real-world dataset from Ivory Coast, this wo...

The recent availability of large-scale call detail record data has substantially improved our ability of quantifying human travel patterns with broad applications in epidemiology. Notwithstanding a number of successful case studies, previous works have shown that using different mobility data sources, such as mobile phone data or census surveys, to...

The idea of a hierarchical spatial organization of society lies at the core of seminal theories in human geography that have strongly influenced our understanding of social organization. Along the same line, the recent availability of large-scale human mobility and communication data has offered novel quantitative insights hinting at a strong geogr...

À l’exemple du selfie, l’exposition de soi sur les réseaux sociaux numériques introduit un clivage au sein du sujet : il se montre et s’observe se montrant. Une distance à soi s’insère dans les pratiques de production de soi. Dans cet article, on propose de caractériser cette distance à soi comme un effet de la socialisation de formes publiques dis...

In this contribution we summarize insights on the geographical veracity of using mobile phone data to create (statistical) indicators. We focus on problems that persist with spatial allocation, spatial delineation and spatial aggregation of information obtained from mobile phone data. For each of the cases, we offer insights from our works on a Fre...

Urban landscapes present a variety of socio-topological environments that are associated to diverse human activities. As the latter affect the way individuals connect with each other, a bound exists between the urban tissue and the mobile communication demand. In this paper, we investigate the heterogeneous patterns emerging in the mobile communica...

An intriguing open question is whether measurements made on Big Data recording human activities can yield us high-fidelity proxies of socio-economic development and well-being. Can we monitor and predict the socio-economic development of a territory just by observing the behavior of its inhabitants through the lens of Big Data? In this paper, we de...

This paper presents a visualization tool for mobile phone usage analysis. Data of mobile phone usage from Portugal is used for demonstration. The visualization runs on two modes: Flow and Intensity. Flow mode displays a 3D animation of mobile phone usage, showing the communication flows between municipalities. Intensity mode displays a 3D animation...

Personal networks can influence human behavior in many aspects. This article presents a correlation analysis of social tie strength and individual behavior concerning mobility and sociality. The study uses a large-scale mobile phone data (110,213 subjects) from which behavior indicators for both mobility and sociality are inferred and used for the...

Analysis of long-distance travel demand has become more relevant in recent times. The reason is the growing share of traffic induced by journeys related to remote activities, which are not part of daily life. In today's mobile world, these journeys are responsible for almost 50 percent of the overall traffic. Traditionally, surveys have been used t...

An intriguing open question is whether measurements made on Big Data recording human activities can yield us high-fidelity proxies of socio-economic development and well-being. Can we monitor and predict the socio-economic development of a territory just by observing the behavior of its inhabitants through the lens of Big Data? In this paper, we de...

Mobile phone operators produce enormous amounts of data. In this paper we present applications performed with a dataset (communication events + handover and Location Area Up-date) collected by the operator Orange from 31 March to 11 April 2009 for the whole Paris Region. Trips are deduced from the spatio-temporal trajectory of devices through a hyp...

Big Data offer nowadays the potential capability of creating a digital nervous system of our society, enabling the measurement, monitoring and prediction of relevant aspects of socioeconomic phenomena in quasi real time. This potential has fueled, in the last few years, a growing interest around the usage of Big Data to support official statistics...

Les enregistrements numériques des interactions humaines couplés avec l’information géographique nous permettent de découvrir des «frontières sociales» dans les relations entre les groupes qui composent nos sociétés. Au-delà des frontières physiques et administratives, ces frontières invisibles émergent des échanges réels entre les usagers du mobil...

Beyond physical borders, “invisible borders” limit interaction between specific groups of people. These “social borders” are historically and socially constructed and result from a wide range of factors such as cultural differences, absence of connecting infrastructure, or even rivalry and prejudice. Insights into such borders can help us understan...

The idea of a hierarchical spatial organization of society lies at the core of seminal theories in human geography that have strongly influenced our understanding of social organization. In the same line, the recent availability of large-scale human mobility and communication data has offered novel quantitative insights hinting at a strong geograph...

Wi-Fi offloading is one of the most effective approaches to relieve the cellular radio access from part of the burgeoning mobile demand. To date, Wi-Fi offloading has been mainly leveraged in limited contexts, such as home, office or campus environments. In this paper, we investigate the scaling properties of Wi-Fi offloading, by studying how it wo...

This paper proposes a methodology for using mobile telephone-based sensor data for detecting spatial and temporal differences in everyday activities in cities. Mobile telephone-based sensor data has great applicability in developing urban monitoring tools and smart city solutions. The paper outlines methods for delineating indicator points of tempo...

The appearance of large geolocated communication datasets has recently increased our understanding of how social networks relate to their physical space. However, many recurrently reported properties, such as the spatial clustering of network communities, have not yet been systematically tested at different scales. In this work we analyze the socia...

Wi-Fi technology has always been an attractive solution for catering the increasing data demand in mobile networks because of the availability of Wi-Fi networks, the high bit rates they provide, and the lower cost of ownership. However, the legacy WiFi technology lacks of seamless interworking between Wi-Fi and mobile cellular networks on the one h...

Wi-Fi technology has always been an attractive solution for catering the increasing data demand in mobile networks because of the availability of Wi-Fi networks, the high bit rates they provide, and the lower cost of ownership. However, the legacy WiFi technology lacks of seamless interworking between Wi-Fi and mobile cellular networks on the one h...

The D4D-Senegal challenge is an open innovation data challenge on anonymous call patterns of Orange's mobile phone users in Senegal. The goal of the challenge is to help address society development questions in novel ways by contributing to the socio-economic development and well-being of the Senegalese population. Participants to the challenge are...

The spatial dissemination of a directly transmitted infectious disease in a population is driven by population movements from one region to another allowing mixing and importation. Public health policy and planning may thus be more accurate if reliable descriptions of population movements can be considered in the epidemic evaluations. Next to censu...

A present issue in the evolution of mobile cellular networks is determining whether, how and where to deploy adaptive content and cloud distribution solutions at the base station and backhauling network level. Intuitively, an adaptive placement of content and computing resources in the most crowded regions can grant important traffic offloading, impr...

In this paper, a model (called the elliptic model) is proposed to estimate the number of social ties between two locations using population data in a similar manner to how transportation research deals with trips. To overcome the asymmetry of transportation models, the new model considers that the number of relationships between two locations is in...

Lieu : Institut National d’Histoire de l’Art (INHA)

Mobile communication technologies pervade our society and existing wireless networks are able to sense the movement of people, generating large volumes of data related to human activities, such as mobile phone call records. At the present, this kind of data is collected and stored by telecom operators infrastructures mainly for billing reasons, yet...

Nous présentons une méthode de génération de matrices de flux Origine-Destination réalisée à partir de l’exploitation de traces spatio-temporelles de téléphones portables. La méthode s’appuie sur une procédure de filtrage temporel fondée sur un algorithme de décomposition empirique du signal (Empirical Mode Decomposition) ; elle tient compte de l’h...

A longitudinal survey in Poland Dominik Batorski, Zbigniew Smoreda Drawing on the results of the nation-wide survey on the living conditions of individuals and households in Poland, the authors analyse data for 2003 and 2005 on the diffusion and use of ICT. These longitudinal data allow for detailed analysis of the Internet drop-out phenomenon. Eve...

Human mobility is differentiated by time scales. While the mechanism for long time scales has been studied, the underlying mechanism on the daily scale is still unrevealed. Here, we uncover the mechanism responsible for the daily mobility patterns by analysing the temporal and spatial trajectories of thousands of persons as individual networks. Usi...

Mobile cloud computing is a new rapidly growing field. In addition to the conventional fashion that mobile clients access cloud services as in the well-known client/server model, existing work has proposed to explore cloud functionalities in another perspective - offloading part of the mobile codes to the cloud for remote execution in order to opti...

In the past few years, mobile network data are considered as a useful complementary source of information for human mobility research. Mobile phone datasets contain massive amount of spatiotemporal localization of millions of users. The analyze of such huge amount of data for mobility studies reveals many issues such as time computation, users samp...

In this paper, we will review several alternative methods of collecting data from mobile phones for human mobility analysis. We will briefly describe cellular phone network architecture and the location data it can provide, and will discuss two types of data collection: active and passive localization. Active localization is something like a person...

Purpose — In this chapter, we will review several alternative methods of collecting data from mobile phones for human mobility analysis. We propose considering cellular network location data as a useful complementary source for human mobility research and provide case studies to illustrate the advantages and disadvantages of each method. Methodolo...

Human mobility analysis is an important issue in social sciences, and mobility data are among the most sought-after sources of information in ur- Data ban studies, geography, transportation and territory management. In network sciences mobility studies have become popular in the past few years, especially using mobile phone location data. For prese...