Bonner Online-Bibliographie zur Comicforschung
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Dunst, Alexander, Rita Hartel und Jochen Laubrock: "The Graphic Narrative Corpus (GNC). Design, Annotation, and Analysis for the Digital Humanities." In: 1st International Workshop on Computational Document Forensics. IWCDF 2017. Hrsg. v. Randall Bilof. Bd. 3. Piscataway: The Institute of Electrical and Electronics Engineers, 2017, S. 15–20. 
Added by: joachim (06 Sep 2018 10:48:05 Europe/Berlin)   Last edited by: joachim (06 Sep 2018 10:57:48 Europe/Berlin)
Resource type: Book Article
Languages: englisch
DOI: 10.1109/ICDAR.2017.286
BibTeX citation key: Dunst2017
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Categories: General
Keywords: Comicforschung, Digitalisierung, Kognition
Creators: Bilof, Dunst, Hartel, Laubrock
Publisher: The Institute of Electrical and Electronics Engineers (Piscataway)
Collection: 1st International Workshop on Computational Document Forensics. IWCDF 2017
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Abstract
Developed for an interdisciplinary DH project, the Graphic Narrative Corpus (GNC) is the first digital corpus of graphic novels, memoirs, and non-fiction written in English. It currently includes 160 book-length titles and will grow to around 250 graphic narratives by 2018. In contrast to collections such as Manga109, the eBDtheque, and the Iyyer corpus, the GNC was conceived to serve both the research needs of humanities and social science scholars and as a data set for computational analysis. The GNC has been constructed as a stratified monitor corpus that balances different historical periods, geographical origin, literary genres, and the gender and ethnic background of authors. Based on an extension of John Walsh’s XML-dialect CBML and editor software developed for the corpus, annotation combines a focus on the first ten pages of each title and sample annotation of full-length books. XML-annotation currently includes visual objects, as well as word-image and character relations (panels, characters, balloons, captions, text, interaction types). In addition, we also provide eye-tracking data for annotated titles. Information about the corpus and sample visualizations can be found at: https://groups.uni-paderborn.de/graphic-literature/gncorpus/corpus.php.
  
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