Diachronic Topics in New High German Poetry
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.
Code (0)
등록된 구현이 없습니다.
Tasks
Authorship AttributionTopic ModelsVocal Bursts Intensity PredictionMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Semantic Change and Emerging Tropes In a Large Corpus of New High German Poetry
Due to its semantic succinctness and novelty of expression, poetry is a great test bed for semantic change analysis. However, so far there is a scarcity of large diachronic corpora. Here, we provide a large corpus of Ger…
Supervised Rhyme Detection with Siamese Recurrent Networks
We present the first supervised approach to rhyme detection with Siamese Recurrent Networks (SRN) that offer near perfect performance (97{\%} accuracy) with a single model on rhyme pairs for German, English and French, a…
Binary ClassificationGeneral ClassificationMapping Topic Evolution Across Poetic Traditions
Poetic traditions across languages evolved differently, but we find that certain semantic topics occur in several of them, albeit sometimes with temporal delay, or with diverging trajectories over time. We apply Latent D…
Diachronic Analysis of German Parliamentary Proceedings: Ideological Shifts through the Lens of Political Biases
We analyze bias in historical corpora as encoded in diachronic distributional semantic models by focusing on two specific forms of bias, namely a political (i.e., anti-communism) and racist (i.e., antisemitism) one. For …
Diachronic Word EmbeddingsWord EmbeddingsALBERTI, a Multilingual Domain Specific Language Model for Poetry Analysis
The computational analysis of poetry is limited by the scarcity of tools to automatically analyze and scan poems. In a multilingual settings, the problem is exacerbated as scansion and rhyme systems only exist for indivi…
Language ModelingLanguage ModellingLarge Language Model