LNSW15

Abstract:

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.

Type: Article

Author: Matthias Lemke, Andreas Niekler, Gary S. Schaal, Gregor Wiedemann
Title: Content Analysis between Quality and Quantity. Fulfilling Blended-Reading Requirements for the Social Sciences with a Scalable Text Mining Infrastructure
Journal: Datenbank Spektrum
Year: 2015
Pages:1-8
@ARTICLE{LNSW15,
AUTHOR = {Matthias Lemke, Andreas Niekler, Gary S. Schaal, Gregor Wiedemann},
TITLE = {Content Analysis between Quality and Quantity. Fulfilling Blended-Reading Requirements for the Social Sciences with a Scalable Text Mining Infrastructure},
JOURNAL = {Datenbank Spektrum},
YEAR = {2015},
PAGES = {1-8}
}