Visualizing Temporal-Thematic Patterns in Text Collections

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dc.contributor.authorKnabben, Moritzen_US
dc.contributor.authorBaumann, Martinen_US
dc.contributor.authorBlascheck, Tanjaen_US
dc.contributor.authorErtl, Thomasen_US
dc.contributor.authorKoch, Steffenen_US
dc.contributor.editorAndres, Bjoern and Campen, Marcel and Sedlmair, Michaelen_US
dc.date.accessioned2021-09-25T16:36:21Z
dc.date.available2021-09-25T16:36:21Z
dc.date.issued2021
dc.description.abstractVisualizing the temporal evolution of texts is relevant for many domains that seek to gain insight from text repositories. However, existing visualization methods for text collections do not show fine-grained temporal-thematic patterns. Therefore, we developed and analyzed a new visualization method that aims at uncovering such patterns. Specifically, we project texts to one dimension, which allows positioning texts in a 2D diagram of projection space and time. For projection, we employed two manifold learning algorithms: the self-organizing map (SOM) and UMAP. To assess the utility of our method, we experimented with real-world datasets and discuss the resulting visualizations. We find our method facilitates relating patterns and extracting associated texts beyond what is possible with previous techniques. We also conducted interviews with historians to show that our prototypical system supports domain experts in their analysis tasks.en_US
dc.description.sectionheadersVisual Data Science
dc.description.seriesinformationVision, Modeling, and Visualization
dc.identifier.doi10.2312/vmv.20211366
dc.identifier.isbn978-3-03868-161-8
dc.identifier.pages9-16
dc.identifier.urihttps://doi.org/10.2312/vmv.20211366
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vmv20211366
dc.publisherThe Eurographics Associationen_US
dc.subjectApplied computing
dc.subjectDocument searching
dc.subjectInformation systems
dc.subjectSearch interfaces
dc.subjectHuman centered computing
dc.subjectVisualization techniques
dc.titleVisualizing Temporal-Thematic Patterns in Text Collectionsen_US
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