This volume presents a selection of articles which explore methodological and applicative aspects of textual data analysis. Divided into four parts, it begins by focusing on statistical methods, and then moves on to problems in quantitative language processing. After discussing the challenging task of text mining in relation to emotional and sentiment analyses, the book concludes with a collection of studies in the social sciences and public health which apply textual data analysis methods.

The refereed contributions were originally presented at the 16th International Conference on Statistical Analysis of Textual Data (JADT 2022), which took place in Naples, Italy, on July 6-8, 2022. The biennial JADT meeting discusses theories, problems, and practical uses of textual data analysis in various fields, sharing a quantitative approach to the study of lexical, textual, pragmatic or discursive features of information expressed in natural language.

About the Author

Giuseppe Giordano is an Associate Professor of Statistics at the Department of Political and Social Studies, University of Salerno, Italy. He teaches Statistics and Analytics for the Social Sciences. His research interests are mainly in Multidimensional Data Analysis, Social Network Analysis, and Analysis of Complex Data Structures with a focus on real problems emerging in several applicative fields.

Michelangelo Misuraca is an Associate Professor of Statistics for Social Sciences at the Department of Business Administration and Law, University of Calabria, Italy. He teaches Statistics for Social Sciences and Textual Statistics at the University of Calabria and at the University of Naples Federico II. He is a fellow of the Italian Statistical Society (SIS) and of the Royal Statistical Society (RSS). His primary research interests are in the domain of Text Mining and Social Media Mining

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