Lemke, MatthiasNiekler, AndreasSchaal, Gary S.Wiedemann, Gregor2018-01-102018-01-1020152015https://dl.gi.de/handle/20.500.12116/11730Social 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.Blended ReadingCorpus LinguisticsMixed MethodsQualitative AnalysisText MiningText/Journal Article1610-1995