Author:
Düring Marten,Romanello Matteo,Ehrmann Maud,Beelen Kaspar,Guido Daniele,Deseure Brecht,Bunout Estelle,Keck Jana,Apostolopoulos Petros
Abstract
Text Reuse reveals meaningful reiterations of text in large corpora. Humanities researchers use text reuse to study, e.g., the posterior reception of influential texts or to reveal evolving publication practices of historical media. This research is often supported by interactive visualizations which highlight relations and differences between text segments. In this paper, we build on earlier work in this domain. We present impresso Text Reuse at Scale, the to our knowledge first interface which integrates text reuse data with other forms of semantic enrichment to enable a versatile and scalable exploration of intertextual relations in historical newspaper corpora. The Text Reuse at Scale interface was developed as part of the impresso project and combines powerful search and filter operations with close and distant reading perspectives. We integrate text reuse data with enrichments derived from topic modeling, named entity recognition and classification, language and document type detection as well as a rich set of newspaper metadata. We report on historical research objectives and common user tasks for the analysis of historical text reuse data and present the prototype interface together with the results of a user evaluation.
Subject
Artificial Intelligence,Information Systems,Computer Science (miscellaneous)
Reference26 articles.
1. “Towards a historical text re-use detection,”;Büchler,2014
2. Reprinting, circulation, and the network author in antebellum newspapers;Cordell;Am. Liter. Hist,2015
3. Impresso inspect and compare: Visual comparison of semantically enriched historical newspaper articles;Düring;Information,2021
4. Lajos kossuth and the transnational news: a computational and multilingual approach to digitized newspaper collections;Keck;Media History,2022
5. “‘Shakespeare in the Vectorian Age'—An evaluation of different word embeddings and NLP parameters for the detection of Shakespeare quotes,”;Liebl,2020
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献