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Content Analysis between Quality and Quantity

Fulfilling Blended-Reading Requirements for the Social Sciences with a Scalable Text Mining Infrastructure


Social science research using Text Mining tools requires—due to the lack of a canonical heuristics in the digital humanities—a blended reading approach. Integrating quantitative and qualitative analyses of complex textual data progressively, blended reading brings up various requirements for the implementation of Text Mining infrastructures. The article presents the Leipzig Corpus Miner (LCM), developed in the joint research project ePol—Post-Democracy and Neoliberalism and responding to social science research requirements. The functionalities offered by the LCM may serve as best practice of processing data in accordance with blended reading.

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ePol is a joint research project of the Institute for Political Science, specialization on Political Theory at Helmut-Schmidt-University Hamburg (Prof. Dr. Gary Schaal) and the Natural Language Processing Group, Department of Computer Science, University of Leipzig (Prof. Dr. Gerhard Heyer). The project is funded by the Federal ministry of education and research (BMBF; FKZ 01UG1231A and B).

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Correspondence to Matthias Lemke.

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Lemke, M., Niekler, A., Schaal, G. et al. Content Analysis between Quality and Quantity. Datenbank Spektrum 15, 7–14 (2015).

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  • Text Mining
  • Qualitative Analysis
  • Blended Reading
  • Mixed Methods
  • Corpus Linguistics