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This three-day training school organised by the CLS INFRA project focused on dynamic collections of literary texts manipulated programmatically. Learners will learn to find, evaluate, and select corpora using tools like CLSCor and DraCor, and gain skills in Python, Jupyter Notebooks, API querying, Linked Open Data, and Digital Literary Network Analysis. The training addresses reproducibility using Docker, promoting transparent, replicable research in Computational Literary Studies.

This resource from the CLS INFRA project offers an introduction to several research areas and issues that are prominent withinComputational Literary Studies (CLS), including authorship attribution, literary history, literary genre, gender in literature, and canonicity/prestige, as well as to several key methodological concerns that are of importance when performing research in CLS.