Enrica Amaturo Editor

Carlo Natale Lauro is Professor Emeritus of Statistics at the University of Naples Federico II, where he was Chair of the Ph.D. course on computational statistics (1988-2014). He was President of the International Association for Statistical Computing and International Federation of Classification Societies. His main scientific interests include data science, multivariate analysis, computational statistics and data mining.

Enrica Amaturo is Full Professor of Sociology and Head of the Department of Social Sciences of the University of Naples Federico II. She is President of the Italian Sociological Association and was a member of the Italian Commission on Social Exclusion (1999-2001; 2007-2011). Her main interests are methods for the analysis of new media, mixed-methods research and the analysis of social exclusion.

Biagio Aragona is Assistant Professor of Sociology at the Department of Social Sciences of the University of Naples Federi

co II, where he teaches social research methods and advanced methods for quantitative research. His research activities primarily involve the use of statistical sources for the analysis of social inequalities and the analysis of the challenges and opportunities that new data offer for the social sciences.

Maria Gabriella Grassia is Associate Professor of Social Statistics at the Department of Social Sciences of the University of Naples Federico II, where she also serves on the research committee for the Ph.D. program on social science and statistics. From 2008 to 2012, she was a Council Officer of the Italian Statistical Society. Her research areas include multivariate analysis, text mining and composite indicators.

Marina Marino is Associate Professor of Statistics at the Department of Social Sciences of the University of Naples Federico II, where she is also a member of the research committee for the Ph.D. program on social Sci

ence and statistics. Her chief research areas are computational statistics, data mining, classification and clustering, statistical analysis of interval-valued data and composite indicators.