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Visually Analyzing Topic Change Points in Temporal Text Collections
Krause, Cedric; Rieger, Jonas; Flossdorf, Jonathan; u. a. (2023): „Visually Analyzing Topic Change Points in Temporal Text Collections“. In: Eindhoven: The Eurographics Association S. 97–105, doi: 10.2312/vmv.20231231.
Author:
Title of the compilation:
Vision, Modeling, and Visualization
Editors:
Grosch, Thorsten
Guthe, Michael
Publisher Information:
Year of publication:
2023
Pages:
ISBN:
978-3-03868-232-5
Language:
English
DOI:
Abstract:
Texts are collected over time and reflect temporal changes in the themes that they cover. While some changes might slowly evolve, other changes abruptly surface as explicit change points. In an application study for a change point extraction method based on a rolling Latent Dirichlet Allocation (LDA), we have developed a visualization approach that allows exploring such change points and related change patterns. Our visualization not only provides an overview of topics, but supports the detailed exploration of temporal developments. The interplay of general topic contents, development, and similarities with detected change points reveals rich insights into different kinds of change patterns. The approach comprises a combination of views including topic timeline representations with detected change points, comparative word clouds, and temporal similarity matrices. In an interactive exploration, these views adapt to selected topics, words, or points in time. We demonstrate the use cases of our approach in an in-depth application example involving statisticians.
GND Keywords: ;
Visualisierung
Textkorpus
Keywords:
Text Collections
DDC Classification:
RVK Classification:
Peer Reviewed:
Yes:
International Distribution:
Yes:
Type:
Contribution to an Articlecollection
Activation date:
November 10, 2023
Versioning
Question on publication
Permalink
https://fis.uni-bamberg.de/handle/uniba/91690