Well-being&Economy workshop

at the Lipari International Summer School for Scientific Research 


Date: 22th July

Location: Hotel Giardino sul Mare, Via Maddalena -LIPARI-

Free registration by email: lipariworkshop@sobigdata.eu


Luca Pappalardo

Aims and scope 

Big Data, the masses of digital breadcrumbs produced by the information technologies that humans use in their daily activities, allow us to scrutinize individual and collective behavior at an unprecedented scale, detail, and speed. Building on this opportunity we have the potential capability of creating a digital nervous system of our society, enabling the measurement, monitoring and prediction of relevant aspects of the socio-economic structure in quasi real time. An intriguing question is whether and how measurements made on Big Data can yield high-fidelity proxies of socio-economic development and well-being. Can we monitor and possibly predict the socio-economic development of our societies just by observing human behavior through the lens of Big Data?
In this workshop we address this topic from different perspectives, presenting part of the work that has been developed within the SoBigData European infrastructure.


15:00 - 15:15

Luca Pappalardo: Opening

15:15 - 16:00

Roberto Trasarti: The SoBigData Project

15:45 - 16:45 

Guido Caldarelli: Structure and Dynamics of Financial Networks
In this talk, the speaker will present a brief overview of the application of Network Science made so far and a perspective on future activities. Particular attention will be devoted to the study of financial markets, in particular how to assess the propagation of distress in the interbank network, what is the role of cycles in the stability of the structure, how to deal with partial or incomplete information.

Alessio Rossi & Paolo Cintia: Predicting injuries of professional soccer players with GPS data and machine learning
Injuries have a great impact on professional soccer, due to their large influence on team performance and the considerable costs of rehabilitation for players. The speakers will show that, by using GPS tracking technology, it is possible to collect data describing the training workload of players in a professional soccer club during a season and create accurate and interpretable injury forecasters, opening a novel perspective on injury prevention and providing a set of simple and practical rules for evaluating and interpreting the complex relations between injury risk and training performance in professional soccer.

16:45 - 17:15 - Coffee Break

17:15 - 18:35

Vasiliki Voukelatou: Big Data and Subjective Well-being
In recent years the empirical science of subjective well-being, popularly referred to as happiness or satisfaction, has grown enormously. In this talk, the speaker will present a brief review of the traditional predictors of subjective well-being and their association with good health and longevity, better social relationships, work performance and creativity. Moreover, it will be shown how Big Data sources, such as mobile phones and social media, can be used nowadays as novel indicators of subjective well-being.

Gianbiagio Curato: Analyzing a GKG network of global news on systemic risk
It will be presented the structure of a Global Knowledge Graph (GKG) provided by the GDELT Project. The network structure measures "media contextualization" over a given topic. The weighted network is defined by the co-occurrences of institutional entities in global news regarding the keywords (systemic,risk) in a financial context. The use of a disparity filter to reduce the network can lead to disassortative network structures.

Dirk Helbing: Nowcasting well-being in societies: at the crossroads of big data, network science, and complex systems
Dirk Helbing is Professor of Computational Social Science at the Department of Humanities, Social and Political Sciences and affiliate of the Computer Science Department at ETH Zurich. His main interest is bringing modeling and computer simulation of social processes and phenomena together with related empirical, experimental, and data-driven work. 

Francesca Pratesi: FAIR: ethics, data protection, and intellectual property law on-line course for Data Scientists
A Corse developed this in order to make sure that all users are familiar with the basic elements about: ethics, data protection, and intellectual property law. The data scientist using the SoBigData infrastructure has the responsibility to get acquainted with the fundamental ethical aspects relating to his/her research and to be aware that using the data he/she can find here will make him/her a "data controller".

18:35 - 18:45

Luca Pappalardo: Wrap-up and Closing


Slides of the talks can be found here