Druck auf Anfrage Neuware - Printed after ordering - Gregor Wiedemann evaluates text mining applications for social science studies with respect to conceptual integration of consciously selected methods, systematic optimization of algorithms and workflows, and methodological reflections relating to empirical research. In an exemplary study, he introduces workflows to analyze a corpus of around 600,000 newspaper articles on the subject of 'democratic demarcation' in Germany. He provides a valuable resource for innovative measures to social scientists and computer scientists in the field of applied natural language processing.

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Bibliographic Details

Title: Text Mining for Qualitative Data Analysis in the Social Sciences : A Study on Democratic Discourse in Germany
Publisher: Springer Fachmedien Wiesbaden
Publication Date: 2016
Language: English
ISBN 10: 3658153083
ISBN 13: 9783658153083
Binding: Taschenbuch
Condition: Neu
Dimensions: 210 millimeters width by 148 millimeters height by 17 millimeters depth
Weight: 406 grams

About this title

Synopsis

Gregor Wiedemann evaluates text mining applications for social science studies with respect to conceptual integration of consciously selected methods, systematic optimization of algorithms and workflows, and methodological reflections relating to empirical research. In an exemplary study, he introduces workflows to analyze a corpus of around 600,000 newspaper articles on the subject of “democratic demarcation” in Germany. He provides a valuable resource for innovative measures to social scientists and computer scientists in the field of applied natural language processing.

About the Author

Gregor Wiedemann holds a doctoral degree from Leipzig University, Germany. He is the coordinator of the discipline-specific working groups in the CLARIN-D project, which develops a European virtual research infrastructure for digital language data analysis in the social sciences and humanities.

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