Overview
- Presents modern statistical analysis methods for textual data
- Showcases applications in sociology, psychology, politics, business and economics
- Adopts a multidisciplinary approach to textual data analysis
Part of the book series: Studies in Classification, Data Analysis, and Knowledge Organization (STUDIES CLASS)
Included in the following conference series:
Conference proceedings info: JADT 2022.
Access this book
Tax calculation will be finalised at checkout
Other ways to access
About this book
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.
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.
Similar content being viewed by others
Table of contents (31 papers)
-
Front Matter
-
Statistical Methods for Textual Data Analysis
-
Front Matter
-
-
Advances in Language Processing
-
Front Matter
-
-
Emotional and Sentiment Analyses
-
Front Matter
-
Other volumes
-
New Frontiers in Textual Data Analysis
Editors and Affiliations
About the editors
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
Accessibility Information
PDF accessibility summary
This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com.
EPUB accessibility summary
This ebook is designed with accessibility in mind, aiming to meet the ePub Accessibility 1.0 AA and WCAG 2.0 Level AA standards. Its features include described images and other non-text content, screenreader-friendly navigation and accessible math. Math is represented either as MathML, LaTeX or in images. If math is represented as image, Alt Text might not be present. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com.
Bibliographic Information
Book Title: New Frontiers in Textual Data Analysis
Editors: Giuseppe Giordano, Michelangelo Misuraca
Series Title: Studies in Classification, Data Analysis, and Knowledge Organization
DOI: https://doi.org/10.1007/978-3-031-55917-4
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
Softcover ISBN: 978-3-031-55916-7Published: 24 September 2024
eBook ISBN: 978-3-031-55917-4Published: 23 September 2024
Series ISSN: 1431-8814
Series E-ISSN: 2198-3321
Edition Number: 1
Number of Pages: XI, 396
Number of Illustrations: 30 b/w illustrations, 99 illustrations in colour
Topics: Statistics for Social Sciences, Humanities, Law, Data Mining and Knowledge Discovery, Natural Language Processing (NLP), Statistical Theory and Methods, Statistics for Business, Management, Economics, Finance, Insurance
Keywords
- Textual Data Analysis
- Statistical Analysis of Textual Data
- Text Mining
- Text Analytics
- Emotional Text Mining
- Sentiment Analysis
- Natural Language Processing
- Social Media Mining
- Applications in the Social Sciences
- Applications in Public Health
- Classification
- Clustering
- Deep Learning
- Network Analysis
- Latent Dirichlet Allocation
- Data Mining