Location: Hotel Giardino sul Mare, Via Maddalena -LIPARI-
Free registration by email: email@example.com
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.
Luca Pappalardo: Opening
Roberto Trasarti: The SoBigData Project
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.
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.
Adriano Fazzone: Algorithms for organizing human experts
Despite the improvement of AI in the last decades, there are still tasks very hard for machines, but easy for humans. Crowdsourcing is a computational paradigm that is successfully used to address problems that require the solution of these types of tasks, by involving human workers in the key steps of the computation. An important characteristic of human workers is their uniqueness: different workers have different profiles and different abilities in solving tasks. In the two contributions collected in this talk, we developed new algorithmic solutions, in the field of Crowdsourcing, that exploit the different level of expertise of workers.
Panel: “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.
Salvatore Rinzivillo is researcher at the Institute of Information Sciences and Technology (ISTI) at the Italian National Research Council (CNR). Salvatore is expert on the analysis of human mobility through Big Data and the impact of human movements on the electrificability of private vehicles.
Guido Caldarelli is one of the leading scholar in Network Science. He is a statistical physicist and currently full professor in Theoretical Physics at IMT School for Advanced Studies Lucca. His research focuses now mainly on the study of the application of network science, especially the study of financial markets through the tools of network theory.
Luca Pappalardo: Wrap-up and Closing