Opening up to Big Data: Computer-Assisted Analysis of Textual Data in Social Sciences


  • Gregor Wiedemann Universität Hamburg



qualitative data analysis, quantitative text analysis, text mining, computer-assisted text analysis, CAQDAS, mixed methods, corpus linguistics, lexicometrics, digital humanities, eHumanities, discourse analysis


Two developments in computational text analysis may change the way qualitative data analysis in social sciences is performed: 1. the availability of digital text worth to investigate is growing rapidly, and 2. the improvement of algorithmic information extraction approaches, also called text mining, allows for further bridging the gap between qualitative and quantitative text analysis. The key factor hereby is the inclusion of context into computational linguistic models which extends conventional computational content analysis towards the extraction of meaning. To clarify methodological differences of various computer-assisted text analysis approaches the article suggests a typology from the perspective of a qualitative researcher. This typology shows compatibilities between manual qualitative data analysis methods and computational, rather quantitative approaches for large scale mixed method text analysis designs.



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Author Biography

Gregor Wiedemann, Universität Hamburg

Gregor WIEDEMANN studied political science and computer science in Leipzig. Currently he is working on his doctoral thesis about the application of computer-assisted approaches for qualitative data analysis in social sciences. As team member of the Natural Language Processing Group at the University of Leipzig he is involved in an interdisciplinary research project which investigates the evolvement of political justifications in the German public media between 1949 and 2011 (ePol project.




How to Cite

Wiedemann, G. (2013). Opening up to Big Data: Computer-Assisted Analysis of Textual Data in Social Sciences. Forum Qualitative Sozialforschung Forum: Qualitative Social Research, 14(2).



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