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Authors: Andreas Weiler ; Michael Grossniklaus and Marc H. Scholl

Affiliation: University of Konstanz, Germany

ISBN: 978-989-758-088-8

Keyword(s): Story Visualization, Text Data Streams, Twitter.

Related Ontology Subjects/Areas/Topics: Abstract Data Visualization ; Computer Vision, Visualization and Computer Graphics ; General Data Visualization ; Information and Scientific Visualization ; Text and Document Visualization ; Time-Dependent Visualization

Abstract: Nowadays, there are plenty of sources generating massive amounts of text data streams in a continuous way. For example, the increasing popularity and the active use of social networks result in voluminous and fast-flowing text data streams containing a large amount of user-generated data about almost any topic around the world. However, the observation and tracking of the ongoing evolution of topics in these unevenly distributed text data streams is a challenging task for analysts, news reporters, or other users. This paper presents “Stor-e- Motion” a shape-based visualization to track the ongoing evolution of topics’ frequency (i.e., importance), sentiment (i.e., emotion), and context (i.e., story) in user-defined topic channels over continuous flowing text data streams. The visualization supports the user in keeping the overview over vast amounts of streaming data and guides the perception of the user to unexpected and interesting points or periods in the text data stream. In this w ork, we mainly focus on the visualization of text streams from the social microblogging service Twitter, for which we present a series of case studies (e.g., the observation of cities, movies, or natural disasters) applied on real-world data streams collected from the public timeline. However, to further evaluate our visualization, we also present a baseline case study applied on the text stream of a fantasy book series. (More)

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Paper citation in several formats:
Weiler, A.; Grossniklaus, M. and Scholl, M. (2015). The Stor-e-Motion Visualization for Topic Evolution Tracking in Text Data Streams.In Proceedings of the 6th International Conference on Information Visualization Theory and Applications - Volume 1: IVAPP, (VISIGRAPP 2015) ISBN 978-989-758-088-8, pages 29-39. DOI: 10.5220/0005292900290039

@conference{ivapp15,
author={Andreas Weiler. and Michael Grossniklaus. and Marc H. Scholl.},
title={The Stor-e-Motion Visualization for Topic Evolution Tracking in Text Data Streams},
booktitle={Proceedings of the 6th International Conference on Information Visualization Theory and Applications - Volume 1: IVAPP, (VISIGRAPP 2015)},
year={2015},
pages={29-39},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005292900290039},
isbn={978-989-758-088-8},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Information Visualization Theory and Applications - Volume 1: IVAPP, (VISIGRAPP 2015)
TI - The Stor-e-Motion Visualization for Topic Evolution Tracking in Text Data Streams
SN - 978-989-758-088-8
AU - Weiler, A.
AU - Grossniklaus, M.
AU - Scholl, M.
PY - 2015
SP - 29
EP - 39
DO - 10.5220/0005292900290039

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