2017/07/11 by Andreas Niekler, Niekler, Andreas, Gregor Wiedemann +3
Computer Science · Social Sciences · #Computation and Language (cs.CL) #Computational and Text Analysis Methods #Data Analysis and Archiving #FOS: Computer and information sciences #Natural Language Processing Techniques
paper · pdf · doi:10.48550/arxiv.1707.03253
openalex publication_date 2017/07/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper presents the "Leipzig Corpus Miner", a technical infrastructure for supporting qualitative and quantitative content analysis. The infrastructure aims at the integration of 'close reading' procedures on individual documents with procedures of 'distant reading', e.g. lexical characteristics of large document collections. Therefore information retrieval systems, lexicometric statistics and machine learning procedures are combined in a coherent framework which enables qualitative data analysts to make use of state-of-the-art Natural Language Processing techniques on very large document collections. Applicability of the framework ranges from social sciences to media studies and market research. As an example we introduce the usage of the framework in a political science study on post-democracy and neoliberalism.