StorylineViz: A [Space, Time, Actors, Motion] Segmentation Method for Visual Text Exploration

Iwona Dudek, Jean-Yves Blaise

Abstract

Supporting knowledge discovery through visual means is a hot research topic in the field of visual analytics in general, and a key issue in the analysis of textual data sets. In that context, the StorylineViz study aims at developing a generic approach to narrative analysis, supporting the identification of significant patterns inside textual data, and ultimately knowledge discovery and sensemaking. It builds on a text segmentation procedure through which sequences of situations are extracted. A situation is defined by a quadruplet of components: actors, space, time and motion. The approach aims at facilitating visual reasoning on the structure, rhythm, patterns and variations of heterogeneous texts in order to enable comparative analysis, and to summarise how the space/time/actors/motion components are organised inside a given narrative. It encompasses issues that are rooted in Information Sciences - visual analytics, knowledge representation – and issues that more closely relate to Digital Humanities – comparative methods and analytical reasoning on textual content, support in teaching and learning, cultural mediation.

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Paper Citation


in Harvard Style

Dudek I. and Blaise J. (2016). StorylineViz: A [Space, Time, Actors, Motion] Segmentation Method for Visual Text Exploration . In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016) ISBN 978-989-758-203-5, pages 21-32. DOI: 10.5220/0006034600210032


in Bibtex Style

@conference{kdir16,
author={Iwona Dudek and Jean-Yves Blaise},
title={StorylineViz: A [Space, Time, Actors, Motion] Segmentation Method for Visual Text Exploration},
booktitle={Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016)},
year={2016},
pages={21-32},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006034600210032},
isbn={978-989-758-203-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016)
TI - StorylineViz: A [Space, Time, Actors, Motion] Segmentation Method for Visual Text Exploration
SN - 978-989-758-203-5
AU - Dudek I.
AU - Blaise J.
PY - 2016
SP - 21
EP - 32
DO - 10.5220/0006034600210032