In this course we start from the basic notions of graph theory and self-similar phenomena in order to correctly analyse large socio-economic networks. From this analysis we then proceed in the description of the modelling for various classes of phenomena and to the correct definition of benchmarks through an approach inspired by classical statistical physics.
Born in Salerno (Italy), I earned my PhD in Computer Science at University of Pisa with the thesis "Human Mobility, Social Networks and Economic Development: a Data Science perspective". In my research, I exploit the power of Big Data to study many aspects of human behavior: the patterns of human mobility, the structure and evolution of complex networks, the patterns of success in sports, and the usage of data-driven measures of human behavior to monitor and predict the economic development of countries, cities, and territories.
Born and raised in Viareggio, Tuscany, Roberto Pellungrini is a PhD student in Computer Science at the University of Pisa. His main research interests concern ethical aspects related to Data Science, in particular regarding Privacy issues. Before winning the PhD scholarship, he attained a Master Degree in Business Informatics with a thesis on Assessing Privacy Risk and Quality in Human Mobility Data.
The internship period is 500 hours, 20 CFU, that single student or a small group of students have to spend in one of the companies and institutions partner of the master, working on an agreed project and under the supervision of a team of tutors composed by the teachers of the master and the management companies.
This course introduces students to the theories, concepts and measures of Social Network Analysis (SNA), that is aimed at characterizing the structure of large-scale Online Social Networks (OSNs). The course presents both classroom teaching to introduce theoretical concepts, and hands-on computer work to apply the theory on real large-scale datasets obtained from OSNs like Facebook and Twitter.
Giovanni Comandè (LLM Harvard Law School USA, Ph.D. Scuola Superiore Sant’Anna) is Full Professor of Private comparative law at Scuola Superiore Sant’Anna where he also studied as ordinary student.
Laureato all’Università Bocconi di Milano, in Discipline economiche e sociali, con la votazione di 110/110 e lode. E' editor di innovazione al Sole 24 Ore e Nova24 (del quale è stato fondatore, che ha guidato dall’ottobre2005 al giugno 2011; e che ha ripreso a guidare dal luglio 2013) e della Vita Nòva, magazine per tablet. E' docente al master di comunicazione della scienza all’Università di Padova e membro del comitato scientifico del master di comunicazione della scienza alla Sissa di Trieste e del master in Big data analytics della Luiss di Roma.
Andrea Marchetti is a technologist in the Institute of Informatics and Telematic (IIT) of CNR Pisa. In 2009 he funded the Web Applications for the Future Internet Group and is responsible of the activity “Social and Semantic Web”. His main research interests are concerning: web of data, digital humanities, data visualization, social media analysis and data journalism. On these issues he produced several publications.
Fosca Giannotti is a senior researcher at the Information Science and Technology Institute of the National Research Council at Pisa, Italy, where she leads the Knowledge Discovery and Data Mining Laboratory – KDD LAB – a joint research initiative with the University of Pisa, founded in 1995, one of the earliest European research groups specifically targeted at data mining and knowledge discovery.
He is a Researcher at the Institute for Informatics and Telematics of CNR. His work focuses on mobile networks and Online and Mobile Social Networks, with emphasis on the study of human social structures in Online Social Networks through the analysis of data on interaction between users. He is co-author of over 100 publications in journals and international conferences, and has received several awards, including four Best Paper Awards at international conferences.
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |
 |