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Conference Paper

Diachronic Topics in New High German Poetry


Haider,  Thomas
Department of Language and Literature, Max Planck Institute for Empirical Aesthetics, Max Planck Society;

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Haider, T. (2019). Diachronic Topics in New High German Poetry. Proceedings of the International Digital Humanities Conference DH2019, Utrecht, https://dev.clariah.nl/files/dh2019/boa/1031.html.

Cite as: https://hdl.handle.net/21.11116/0000-0006-6F90-B
Statistical topic models are increasingly and popularly used by Digital Humanities scholars to perform distant reading tasks on literary data. It allows us to estimate what people talk about. Especially Latent Dirichlet
Allocation (LDA) has shown its usefulness, as it is unsupervised, robust, easy to use, scalable, and it offers interpretable results. In a preliminary study, we apply LDA to a corpus of New High German poetry (textgrid, with 51k poems, 8m token), and use the distribution of topics over documents for a
classification of poems into time periods and for authorship attribution.