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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. Contents • 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 Target Groups • Researchers and students in the fields of social sciences, digital humanities and communication science, scientists interested in innovative text analysis methods, computer scientists in interdisciplinary projects or research fields working with large amounts of textual data 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.
Social sciences. --- Democracy. --- Sociology --- Social Sciences. --- Methodology of the Social Sciences. --- Research Methodology. --- Research. --- Algorithms. --- Algorism --- Algebra --- Arithmetic --- Foundations --- Social sciences --- Sociology-Research. --- Self-government --- Political science --- Equality --- Representative government and representation --- Republics --- Methodology. --- Sociology—Research. --- Behavioral sciences --- Human sciences --- Sciences, Social --- Social science --- Social studies --- Civilization
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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. Contents • 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 Target Groups • Researchers and students in the fields of social sciences, digital humanities and communication science, scientists interested in innovative text analysis methods, computer scientists in interdisciplinary projects or research fields working with large amounts of textual data 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.
Science --- Social sciences (general) --- Sociology --- Political systems --- sociologie --- text mining --- onderzoeksmethoden --- sociale wetenschappen --- democratie --- gegevensanalyse --- methodologieën
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Die Analyse von Sprache ermöglicht Rückschlüsse auf Gesellschaft und Politik. Im Zeitalter digitaler Massenmedien liegt Sprache als maschinenlesbarer Text in einer Menge vor, die ohne Hilfsmittel nicht mehr angemessen zu bewältigen ist. Die maschinelle Auswertung von Textdaten kann in den Sozialwissenschaften, die Text bislang in der Regel qualitativ und weniger quantitativ, also sprachstatistisch, analysieren, wertvolle neue Erkenntnisse liefern. Vor diesem Hintergrund führt der Band in die Verwendung von Text Mining in den Sozialwissenschaften ein. Anhand exemplarischer Analysen eines Korpus von 3,5 Millionen Zeitungsartikeln zeigt er für konkrete Forschungsfragen, wie Text Mining angewandt werden kann. Der Inhalt · Grundlagen: Text und Soziale Wirklichkeit • Blended Reading • Text Mining-Anwendungen zur Analyse qualitativer Daten • Text Mining als Methode · Anwendungen: Neoliberalismus und der Wandel von Gerechtigkeitsdiskursen • Verwissenschaftlichung der Politik • Internationale Organisationen in der deutschen Öffentlichkeit • Rettungsfolter in der Demokratie · Perspektiven: Auf dem Weg zu einer Best Practice? Die Zielgruppen · PolitikwissenschaftlerInnen · ; SozialwissenschaftlerInnen · LinguistInnen Die Herausgeber Dr. Matthias Lemke ist wissenschaftlicher Mitarbeiter am Lehrstuhl für Politikwissenschaft, insbesondere Politische Theorie, der Helmut-Schmidt-Universität/Universität der Bundeswehr Hamburg. Gregor Wiedemann ist wissenschaftlicher Mitarbeiter in der Abteilung Automatische Sprachverarbeitung der Universität Leipzig.
Social sciences. --- Political science. --- Methodology of the Social Sciences. --- Political Science.
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