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New Frontiers in Textual Data Analysis

Giuseppe Giordano (Hrsg.), Michelangelo Misuraca (Hrsg.)

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Springer Nature Switzerland img Link Publisher

Sozialwissenschaften, Recht, Wirtschaft / Methoden der empirischen und qualitativen Sozialforschung

Beschreibung

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.

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Schlagwörter

Latent Dirichlet Allocation, Natural Language Processing, Applications in the Social Sciences, Text Mining, Text Analytics, Textual Data Analysis, Applications in Public Health, Emotional Text Mining, Sentiment Analysis, Data Mining, Social Media Mining, Classification, Deep Learning, Network Analysis, Statistical Analysis of Textual Data, Clustering