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MiMoText is a research project in computational literary studies dealing with new ways to model and analyse literary history and literary historiography. It is based on the idea of extracting statements relevant to literary history from bibliographies, scholarly publications and primary sources, in order to build a shared knowledge network for literary history. We employ methods from information extraction and text mining to obtain large numbers of statements about authors and literary works from our data. Moreover, we use the Linked Open Data paradigm to model, represent and query the information we obtain. We believe our project is a step towards a mode of digital humanities that goes not only beyond small, deeply encoded datasets and their close reading, but also beyond Big Data approaches that cannot always be easily adapted to the humanities. Instead, we propose a third way for digital humanities that develops quantitative methods to create and analyse datasets relevant to research in the humanities that are both larger and smarter than has been customary up until recently. [ABSTRACT FROM AUTHOR]