Big Data Analytics and Social Mining

Big Data at a societal scale are a powerful microscope, which together with Social Mining – the ability of making sense of data – can help us measure, understand and predict many complex socio-economic phenomena. My seminar discusses the novel questions that big data and social mining allow to raise and answer, how a new paradigm for scientific exploration, statistics and policy making is emerging, and the major scientific, technological and societal barriers to be overcome to realize this vision. I will focus on concrete projects with telecom providers and official statistics bureau in Italy and France aimed at measuring, quantifying and possibly predicting key demographic and socio-economic indicators based on nation-wide mobile phone data and other sources of big data: the dynamics of different categories of city users (residents, commuters, visitors) in urban spaces, the level of well-being and economic development at various spatial and temporal scales, the emergence of distinct patterns of human mobility, the diffusion of innovation.

Dino Pedreschi is a Professor of Computer Science at the University of Pisa, and a pioneering scientist in mobility data mining, social network analysis and privacy-preserving data mining. He co-leads with Fosca Giannotti the Pisa KDD Lab - Knowledge Discovery and Data Mining Laboratory http://kdd.isti.cnr.it, a joint research initiative of the University of Pisa and the Information Science and Technology Institute of the Italian National Research Council, one of the earliest research labs centered on data mining. His research focuses on data science, big data analytics and social mining, and their impact on society. He is a founder of graduate courses for the education of interdisciplinary data scientists, and of SoBigData.eu, the H2020 European Research Infrastructure “Social Mining & Big Data Ecosystem”.