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Dataset . 2026
License: CC BY
Data sources: Datacite
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dhd2026

Authors: Kellner, Nils; Lemke, Marc; Henny-Krahmer, Ulrike;
Abstract

This is a repository containing the data and code for our poster "Kombinieren statt neu trainieren. Zur automatisierten Erkennung diegetischen räumlichen Vokabulars mit Hilfe existierender Annotationen und Classifier" addressing the recognition of diegetic spatial vocabulary presented at DHd2026 in Vienna. DFG Priority Program SPP 2207 “Computational Literary Studies“Online: https://gepris.dfg.de/gepris/projekt/402743989 https://dfg-spp-cls.github.io/ Subproject: "Computational Approaches to Narrative Space in 19th and 20th Century Novels" (CANSpiN)Online: https://gepris.dfg.de/gepris/projekt/508056813 https://dfg-spp-cls.github.io/projects_en/2020/01/24/TP-Computational_Approaches_to_Narrative_Space https://www.canspin.uni-rostock.de

Related Organizations
Keywords

Digital Humanities, DHd2026, CANSpiN, Computational Literary Studies, SPP 2207

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average