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International Joint Conference on Computer Vision, Imaging and Computer Graphics

VISIGRAPP 2016: Computer Vision, Imaging and Computer Graphics Theory and Applications pp 220–241Cite as

Visual Analysis of Character and Plot Information Extracted from Narrative Text

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 693))

Abstract

The study of novels and the analysis of their plot, characters and other information entities are complex and time-consuming tasks in literary science. The digitization of literature and the proliferation of electronic books provide new opportunities to support these tasks with visual abstractions. Methods from the field of computational linguistics can be used to automatically extract entities and their relations from digitized novels. However, these methods have known limitations, especially when applied to narrative text that does often not follow a common schema but can have various forms. Visualizations can address the limitations by providing visual clues to show the uncertainty of the extracted information, so that literary scholars get a better idea of the accuracy of the methods. In addition, interaction can be used to let users control and adapt the extraction and visualization methods according to their needs. This paper presents ViTA, a web-based approach that combines automatic analysis methods with effective visualization techniques. Different views on the extracted entities are provided and relations between them across the plot are indicated. Two usage scenarios show successful applications of the approach and demonstrate its benefits and limitations. Furthermore, the paper discusses how uncertainty might be represented in the different views and how users can be enabled to adapt the automatic methods.

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Notes

  1. 1.

    A video and demo of the web implementation are available at http://textvis.visualdataweb.org.

  2. 2.

    http://www.gutenberg.org.

  3. 3.

    http://nlp.stanford.edu/software/corenlp.shtml.

  4. 4.

    http://opennlp.apache.org.

  5. 5.

    https://gate.ac.uk/ie/annie.html.

  6. 6.

    http://colorbrewer2.org.

  7. 7.

    https://github.com/mbostock/d3/wiki/Ordinal-Scales#categorical-colors.

  8. 8.

    http://csclub.uwaterloo.ca/~n2iskand/?page_id=13/.

  9. 9.

    http://www.epoetics.de.

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Acknowledgements

We would like to thank our students Sanjeev Balakrishnan, Felix Do, Sebastian Frank, Paul Kuznecov, Vincent Link, Eduard Marbach, Jan Melcher, Christian Richter, Marc Weise, and Marvin Wyrich who implemented the approach in a student project. This work has partly been funded by the German Federal Ministry of Education and Research (BMBF) as part of the ‘ePoetics’ project and as part of the Center for Reflected Text Analysis ‘CRETA’ at University of Stuttgart.

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Authors and Affiliations

  1. Institute for Visualization and Interactive Systems (VIS), University of Stuttgart, Universitätsstraße 38, 70569, Stuttgart, Germany

    Markus John, Steffen Koch, Michael Wörner & Thomas Ertl

  2. Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS), Schloss Birlinghoven, 53757, Sankt Augustin, Germany

    Steffen Lohmann

Authors
  1. Markus John
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  3. Steffen Koch
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  4. Michael Wörner
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  5. Thomas Ertl
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Corresponding author

Correspondence to Markus John .

Editor information

Editors and Affiliations

  1. Escola Superior de Tecnologia do IPS, Setúbal, Portugal

    José Braz

  2. MiraLab, University of Geneva, Carouge, Switzerland

    Nadia Magnenat-Thalmann

  3. LISA - ISTIA, University of Angers, Angers, France

    Paul Richard

  4. Department of Computer Science and Electrical Engineering, Jacobs University, Bremen, Germany

    Lars Linsen

  5. University of Groningen, Groningen, The Netherlands

    Alexandru Telea

  6. Università di Catania, Catania, Italy

    Sebastiano Battiato

  7. Research Innovation Center, Canon U.S.A. Inc., San Jose, California, USA

    Francisco Imai

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John, M., Lohmann, S., Koch, S., Wörner, M., Ertl, T. (2017). Visual Analysis of Character and Plot Information Extracted from Narrative Text. In: Braz, J., et al. Computer Vision, Imaging and Computer Graphics Theory and Applications. VISIGRAPP 2016. Communications in Computer and Information Science, vol 693. Springer, Cham. https://doi.org/10.1007/978-3-319-64870-5_11

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  • DOI: https://doi.org/10.1007/978-3-319-64870-5_11

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