Lorenzo Gabrielli

Lorenzo Gabrielli
Italian National Research Council | CNR · Institute of Information Science and Technology "Alessandro Faedo" ISTI

About

29
Publications
12,108
Reads
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570
Citations
Additional affiliations
August 2010 - October 2015
Italian National Research Council
Position
  • Researcher, Data Scientist

Publications

Publications (29)
Conference Paper
Full-text available
Peacefulness is a principal dimension of well-being, and its measurement has lately drawn the attention of researchers and policy-makers. During the last years, novel digital data streams have drastically changed research in this field. In the current study, we exploit information extracted from Global Data on Events, Location, and Tone (GDELT) dig...
Article
Full-text available
Well-being is an important value for people’s lives, and it could be considered as an index of societal progress. Researchers have suggested two main approaches for the overall measurement of well-being, the objective and the subjective well-being. Both approaches, as well as their relevant dimensions, have been traditionally captured with surveys....
Chapter
Full-text available
Studying migration using traditional data has some limitations. To date, there have been several studies proposing innovative methodologies to measure migration stocks and flows from social big data. Nevertheless, a uniform definition of a migrant is difficult to find as it varies from one work to another depending on the purpose of the study and n...
Article
The availability of mobile phone data has encouraged the development of different data-driven tools, supporting social science studies and providing new data sources to the standard official statistics. However, this particular kind of data are subject to privacy concerns because they can enable the inference of personal and private information. In...
Article
Full-text available
In this paper we investigate the regularities characterizing the temporal purchasing behavior of the customers of a retail market chain. Most of the literature studying purchasing behavior focuses on what customers buy while giving few importance to the temporal dimension. As a consequence, the state of the art does not allow capturing which are th...
Article
Full-text available
Models of human migration provide powerful tools to forecast the flow of migrants, measure the impact of a policy, determine the cost of physical and political frictions and more. Here, we analyse the migration of individuals from and to cities in the US, finding that city to city migration follows scaling laws, so that the city size is a significa...
Conference Paper
This work deals with quantifying skills use, reading, writing, numeracy, and ICT, at work and at home. It aims at contributing to the debate on developing policies transforming "better skills in better jobs, social inclusion and economic growth". Thanks to data collected by the Organization for Economic Cooperation and Development (OECD), we can ob...
Chapter
How do we measure the borders of urban areas and therefore decide which are the functional units of the territory? Nowadays, we typically do that just looking at census data, while in this work we aim to identify functional areas for mobility in a completely data-driven way. Our solution makes use of human mobility data (vehicle trajectories) and c...
Conference Paper
Full-text available
The huge quantity of personal data stored by service providers registering customers daily life enables the analysis of individual fingerprints characterizing the customers' behavioral profiles. We propose a framework for recognizing residents, tourists and occasional shoppers among the customers of a retail market chain. We employ our recognition...
Article
Full-text available
Mobile phones have an unprecedented rate of penetration across the world. Such devices produce a large amount of data that have been used on different domains. In this work, we make use of mobile calls to monitor the presence of individuals region by region. Traditionally, this activity has been conducted by means of censuses and surveys. Nowadays,...
Article
Full-text available
The increasing availability of large amounts of data and digital footprints has given rise to ambitious research challenges in many fields, which spans from medical research, financial and commercial world, to people and environmental monitoring. Whereas traditional data sources and census fail in capturing actual and up-to-date behaviors, Big Data...
Article
Full-text available
Over the last two decades, passively collected data sources, like Global Positioning System (GPS) traces from data loggers and smartphones, have emerged as a very promising source for understanding travel behaviour. Most choice model applications in this context have made use of data collected specifically for choice modelling, which often has high...
Chapter
The paper illustrates basic methods of mobility data mining, designed to extract from the big mobility data the patterns of collective movement behavior, i.e., discover the subgroups of travelers characterized by a common purpose, profiles of individual movement activity, i.e., characterize the routine mobility of each traveler. We illustrate a num...
Article
Full-text available
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...
Conference Paper
Full-text available
Statistical authorities promote and safeguard the production and publication of official statistics that serve the public good. One of their duties is to monitor the presence of individuals region by region. Traditionally this activity has been conducted by means of censuses and surveys. Nowadays technologies open new possibilities such as a contin...
Poster
Full-text available
Several works in literature showed that the purchase behavior of an individual is a reliable proxy for individual wealth and well-being. Official statistics institutes, indeed, base their well-being indicators on surveys regarding the purchase expenditure of individuals within a given territory. These surveys, however, are often not up-to-date, exp...
Article
Full-text available
The timely, accurate monitoring of social indicators, such as poverty or inequality, on a finegrained spatial and temporal scale is a crucial tool for understanding social phenomena and policymaking, but poses a great challenge to official statistics. This article argues that an interdisciplinary approach, combining the body of statistical research...
Article
Full-text available
Can we predict the outcome of future elections? Many politicians wonder if they will be re-elected and often they rely on polls conducted on a small sample of the population. In this work, we propose a data-driven approach that, given the past expenditure of city mayors, considers what are the most important aspects that determine the re-election....
Conference Paper
Full-text available
Nowadays mobile phone data are an actual proxy for studying the users' social life and urban dynamics. In this paper we present the Sociometer, and analytical framework aimed at classifying mobile phone users into behavioral categories by means of their call habits. The analytical process starts from spatio-temporal profiles, learns the different b...
Conference Paper
Big Data originating from the digital breadcrumbs of human activities, sensed as by-product of the technologies that we use for our daily activities, allows us to observe the individual and collective behavior of people at an unprecedented detail. Many dimensions of our social life have big data “proxies”, such as the mobile calls data for mobility...
Chapter
In this work we present an analysis process that exploits mobile phone transaction (trajectory) data to infer a transport demand model for the territory under monitoring. In particular, long-term analysis of individual call traces are performed to reconstruct systematic movements, and to infer an origin-destination matrix. We will show a case study...
Conference Paper
Full-text available
The large availability of mobility data allows us to investigate complex phenomena about human movement. However this adundance of data comes with few information about the purpose of movement. In this work we address the issue of activity recognition by introducing Activity-Based Cascading (ABC) classification. Such approach departs completely fro...
Article
This paper proposes and experiments new techniques to de- Tect urban mobility patterns and anomalies by analyzing trajectories mined from publicly available geo-positioned social media traces left by the citizens (namely Twitter). By collecting a large set of geo-located tweets characterizing a specific urban area over time, we semantically enrich...
Conference Paper
This information about our GSM calls is stored by the TelCo operator in large volumes and with strict privacy constraints making it challenging the analysis of these fingerprints for inferring mobility behavior. This paper proposes a strategy for mobility behavior identification based on aggregated calling profiles of mobile phone users. This compa...
Chapter
Full-text available
This paper proposes and experiments new techniques to detect urban mobility patterns and anomalies by analyzing trajectories mined from publicly available geo-positioned social media traces left by the citizens (namely Twitter). By collecting a large set of geo-located tweets characterizing a specific urban area over time, we semantically enrich th...
Conference Paper
Traditionally, the information about human mobility behavior, called diary, is acquired from volunteers by means of paper-and-pencil surveys. These diaries, representing the mobile activities of individuals, are semantically rich, but lack in spatial and temporal precision. An alternative way is collecting diaries by annotating with activities the...
Chapter
The ability to understand the dynamics of human mobility is crucial for tasks like urban planning and transportation management. The recent rapidly growing availability of large spatio-temporal datasets gives us the possibility to develop sophisticated and accurate analysis methods and algorithms that can enable us to explore several relevant mobil...
Article
Full-text available
The huge quantity of positioning data registered by our mobile phones stimulates several research questions, mainly originating from the combination of this huge quantity of data with the extreme heterogeneity of the tracked user and the low granularity of the data. We propose a methodology to partition the users tracked by GSM phone calls into pro...

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Projects

Projects (4)
Project
We live in an era of unprecedented data, digital footprints created every day by sensors, smartphones, internet, social media, and administrative systems. Digital trace data can be processed using computational methods to model collective behaviours and describe aspects of our society that are already present but not yet captured or quantified. The main objective of the project is to build capacity in accessing and analysing non-traditional data through key partnerships and in coordination with European Commission services. This will clear the path to address concrete policy questions by engaging in a knowledge exchange among all partners, connecting academia with policymakers and the private sector.
Project
SoBigData proposes to create the Social Mining & Big Data Ecosystem: a research infrastructure (RI) providing an integrated ecosystem for ethic-sensitive scientific discoveries and advanced applications of social data mining on the various dimensions of social life, as recorded by “big data”. Building on several established national infrastructures, SoBigData will open up new research avenues in multiple research fields, including mathematics, ICT, and human, social and economic sciences, by enabling easy comparison, re-use and integration of state-of-the-art big social data, methods, and services, into new research.
Project
SoBigData proposes to create the Social Mining & Big Data Ecosystem: a research infrastructure (RI) providing an integrated ecosystem for ethic-sensitive scientific discoveries and advanced applications of social data mining on the various dimensions of social life, as recorded by “big data”. Building on several established national infrastructures, SoBigData will open up new research avenues in multiple research fields, including mathematics, ICT, and human, social and economic sciences, by enabling easy comparison, re-use and integration of state-of-the-art big social data, methods, and services, into new research.