Ehrmanntraut, Anton ; Hagen, Thora ; Jannidis, Fotis ; Konle, Leonard ; Kröncke, Merten ; Winko, Simone (2023)
Modeling and Measuring Short Text Similarities. On the Multi-Dimensional Differences between German Poetry of Realism and Modernism.
In: Journal of Computational Literary Studies, 2022, 1 (1)
doi: 10.26083/tuprints-00023259
Artikel, Zweitveröffentlichung, Verlagsversion
Kurzbeschreibung (Abstract)
This study contributes to the ongoing discussion on how to operationalize text similarity for the purposes of computational literary studies by defining, justifying theoretically and employing a multi-dimensional text model. Additionally, we evaluate a set of strategies to implement this model for very short texts like poetry using a range of methods from weighted sparse vectors up to very recent neural sentence embeddings based on annotations of emotions, genre and similarity. And finally, we show the relevance of using such a complex text model by applying the best method to a research question about the development of early modernism in German poetry. While we can confirm some important hypotheses from literary studies, we are also able to differentiate or relativize others. In particular, our findings do not support the widely held thesis that the change from realism to modernism was a revolutionary ‘rupture’.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2023 |
| Autor(en): | Ehrmanntraut, Anton ; Hagen, Thora ; Jannidis, Fotis ; Konle, Leonard ; Kröncke, Merten ; Winko, Simone |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | Modeling and Measuring Short Text Similarities. On the Multi-Dimensional Differences between German Poetry of Realism and Modernism |
| Sprache: | Englisch |
| Publikationsjahr: | 2023 |
| Ort: | Darmstadt |
| Publikationsdatum der Erstveröffentlichung: | 2022 |
| Verlag: | Universitäts- und Landesbibliothek Darmstadt |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Journal of Computational Literary Studies |
| Jahrgang/Volume einer Zeitschrift: | 1 |
| (Heft-)Nummer: | 1 |
| Kollation: | 30 Seiten |
| DOI: | 10.26083/tuprints-00023259 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/23259 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichung von TUjournals |
| Kurzbeschreibung (Abstract): | This study contributes to the ongoing discussion on how to operationalize text similarity for the purposes of computational literary studies by defining, justifying theoretically and employing a multi-dimensional text model. Additionally, we evaluate a set of strategies to implement this model for very short texts like poetry using a range of methods from weighted sparse vectors up to very recent neural sentence embeddings based on annotations of emotions, genre and similarity. And finally, we show the relevance of using such a complex text model by applying the best method to a research question about the development of early modernism in German poetry. While we can confirm some important hypotheses from literary studies, we are also able to differentiate or relativize others. In particular, our findings do not support the widely held thesis that the change from realism to modernism was a revolutionary ‘rupture’. |
| Freie Schlagworte: | short text, similarity, poetry, modernism, realism |
| Status: | Verlagsversion |
| URN: | urn:nbn:de:tuda-tuprints-232599 |
| Zusätzliche Informationen: | Urspr. Konferenzveröffentlichung/Originally conference publication: 1st Annual Conference of Computational Literary Studies, 01.-02.06.2022, Darmstadt, Germany |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 800 Literatur > 800 Literatur, Rhetorik, Literaturwissenschaft |
| Fachbereich(e)/-gebiet(e): | 02 Fachbereich Gesellschafts- und Geschichtswissenschaften > Institut für Sprach- und Literaturwissenschaft > Digital Philology - Neuere deutsche Literaturwissenschaft 02 Fachbereich Gesellschafts- und Geschichtswissenschaften 02 Fachbereich Gesellschafts- und Geschichtswissenschaften > Institut für Sprach- und Literaturwissenschaft |
| Hinterlegungsdatum: | 21 Feb 2023 10:28 |
| Letzte Änderung: | 27 Feb 2023 12:47 |
| PPN: | |
| Zugehörige Links: | |
| Export: | |
| Suche nach Titel in: | TUfind oder in Google |
 |
Frage zum Eintrag |
Optionen (nur für Redakteure)
 |
Redaktionelle Details anzeigen |
Drucken
Impressum