Carlo Natale Lauro – författare

This volume reflects the state of the art in social data science and comprises a selection of peer-reviewed papers from the 4th International Conference on Data Science and Social Research, DSSR 2024, held in Naples, Italy, March 25–27, 2024. Drawing on statistics and computational methods within data science, it explores the opportunities and challenges that the “data revolution” poses to social research, addressing key areas such as sustainable development, social inequalities, public health, communication, and futures studies.The contributions examine complex social systems and present new social research on human behavior and society, using large datasets gathered from a variety of sources, such as social media and communication systems, or produced through controlled experiments, along with new methodological advancements for extracting social knowledge from large-scale datasets. Methodological, ethical, and digital data quality issues pertaining to social platforms are covered, with a focus on both the study of spatial data as well as sustainability, including sustainable tourism, and integrated systems are examined to take advantage of new sources of social data.

This volume contains revised versions of selected papers presented at the biennial meeting of the Classi?cation and Data Analysis Group (CLADAG) of the Italian Statistical Society, which was held in Macerata, September 12-14, 2007. Carlo Laurochairedthe Scienti?c ProgrammeCommitteeand FrancescoPalumbochaired the Local Organizing Committee. The scienti?c programme scheduled 150 oral presentations and one poster s- sion. Sessions were organised in ?ve plenary sessions, 10 invited paper specialised sessions and 24 solicited paper sessions. Contributed papers and posters were 54 and 12, respectively. Five eminent scholars, who have given important impact in the Classi?cation and Data Analysis ?elds, were invited as keynote speakers, they are H. Bozdogan, S. R. Masera, G. McLachlan, A. Montanari, A. Rizzi. Invited Paper Specialised Sessions focused on the following topics: Knowledge extraction from temporal data models Statistical models with errors-in-covariates Multivariate analysis for microarray data Cluster analysis of complex data Educational processes assessment by means of latent variables models Classi?cation of complex data Multidimensional scaling Statistical models for public policies Classi?cation models for enterprise risk management Model-based clustering It is worth noting that two of the ten specialised sessions were organised by the French (Classi?cation of complex data) and Japanese (Multidimensional scaling) classi?cation societies. The SPC is grateful to professorsOkada (Japan) and Zighed (France), who took charge of the Japanese and French specialised session org- isation, respectively.