Text Mining for Qualitative Data Analysis in the Social Sciences

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.

Study in the field of social sciences Includes supplementary material: sn.pub/extras

Autorentext
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.

Inhalt
Qualitative Data Analysis in a Digital World.- Computer-Assisted Text Analysis in the Social Sciences.- Integrating Text Mining Applications for Complex Analysis.- Democratic Demarcation in Germany.- V-TM A Methodological Framework for Social Sciences.- Integrating Qualitative and Computational Text Analysis.