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Text Mining for Qualitative Data Analysis in the Social Sciences: A Study on Democratic Discourse in Germany (Kritische Studien zur Demokratie)
Gregor Wiedemann
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Description for Text Mining for Qualitative Data Analysis in the Social Sciences: A Study on Democratic Discourse in Germany (Kritische Studien zur Demokratie)
Paperback. Series: Kritische Studien zur Demokratie. Num Pages: 311 pages, 24 black & white illustrations, biography. BIC Classification: JHBC; JPHV. Category: (P) Professional & Vocational. Dimension: 150 x 211 x 21. Weight in Grams: 410.
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.
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.
Product Details
Format
Paperback
Publication date
2016
Publisher
Springer VS
Condition
New
Series
Kritische Studien zur Demokratie
Number of Pages
294
Place of Publication
Weisbaden, Germany
ISBN
9783658153083
SKU
V9783658153083
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About Gregor Wiedemann
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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