Publikation: Advanced Visual Analytics Methods for Literature Analysis
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The volumes of digitized literary collections in various languages increase at a rapid pace, which results also in a growing demand for computational support to analyze such linguistic data. This paper combines robust text analysis with advanced visual analytics and brings a new set of tools to literature analysis. Visual analytics techniques can offer new and unexpected insights and knowledge to the literary scholar. We analyzed a small subset of a large literary collection, the Swedish Literature Bank, by focusing on the extraction of persons’ names, their gender and their normalized, linked form, including mentions of theistic beings (e.g., Gods’ names and mythological figures), and examined their appearance over the course of the novel. A case study based on 13 novels, from the aforementioned collection, shows a number of interesting applications of visual analytics methods to literature problems, where named entities can play a prominent role, demonstrating the advantage of visual literature analysis. Our work is inspired by the notion of distant reading or macroanalysis for the analyses of large literature collections.
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OELKE, Daniela, Dimitrios KOKKINAKIS, Mats MALM, 2012. Advanced Visual Analytics Methods for Literature Analysis. LaTeCH. Avignon, France, 12. Apr. 2012. In: EACL 2012 : Proceedings of the 6 thWorkshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities (LaTeCH 2012) ; 24 April 2012, Avignon, France. Stroudsburg: Association for Computational Linguistics, 2012, pp. 35-44. ISBN 978-1-937284-19-0BibTex
@inproceedings{Oelke2012Advan-22588, year={2012}, title={Advanced Visual Analytics Methods for Literature Analysis}, isbn={978-1-937284-19-0}, publisher={Association for Computational Linguistics}, address={Stroudsburg}, booktitle={EACL 2012 : Proceedings of the 6 thWorkshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities (LaTeCH 2012) ; 24 April 2012, Avignon, France}, pages={35--44}, author={Oelke, Daniela and Kokkinakis, Dimitrios and Malm, Mats} }
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