Baumgartl, T., Sondag, M., Filipov, V., Tuscher, M., Rajendran, S., Miksch, S., Archambault, D., Arleo, A., & Landesberger von Antburg, T. (2026). Survey on Visualization of Information Diffusion over Networks. In A. Abdul-Rahman, M. Angelini, & B. Preim (Eds.), EuroVis 2026: 28th Eurographics Conference on Visualization 2026. https://doi.org/10.1111/cgf.70498
E193-07 - Forschungsbereich Visual Analytics E056-18 - Fachbereich Visual Analytics and Computer Vision Meet Cultural Heritage
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Published in:
EuroVis 2026: 28th Eurographics Conference on Visualization 2026
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Volume:
45/3
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Date (published):
11-Jun-2026
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Event name:
28th Eurographics Conference on Visualization (EuroVis 2026)
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Event date:
8-Jun-2026 - 12-Jun-2026
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Event place:
Nottingham, United Kingdom of Great Britain and Northern Ireland (the)
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Number of Pages:
42
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Peer reviewed:
Yes
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Keywords:
Information Diffusion; Dynamic Networks; Network Visualization; Visualization; Visual Analytics
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Abstract:
Information Diffusion (ID) describes how a value (e.g., a pathogen, a rumor, a packet) spreads through an underlying “medium” network of elements (e.g., a social or computer network). Understanding the information diffusion process is essential to predicting trends, controlling misinformation, and enhancing decision-making as well as communication strategies. Visual Analytics has shown significant potential in supporting comprehension of ID processes in several domains. These approaches vary greatly in their design, both in terms of data and visual encodings. The variety of designs and application domains motivates this survey, which complements existing surveys with a focus on visualization of transmission processes in contrast to other surveys about visualizing networks. This survey defines types of transmission and medium networks, identifies common visualization principles, categorizes them, and identifies gaps–opportunities for future research.
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Project title:
SANE: Visual Analytics für Ereignisdiffusion in Netzwerken: I 6635-N (FWF - Österr. Wissenschaftsfonds) ArtVis: Dynamische Netzwerk für die digitale Kunstgeschichte: P35767-N (FWF - Österr. Wissenschaftsfonds) Visuelle Analytik und Computer Vision treffen auf kulturelles Erbe: DFH 37-N (FWF - Österr. Wissenschaftsfonds)
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Project (external):
German Research Foundation (DFG) BMFTR UK Research and Innovation Engineering and Physical Sciences Research Council (UKRI EPSRC)
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Project ID:
527250730 01ZZ2323J EP/V033670/1
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Research Areas:
Visual Computing and Human-Centered Technology: 100%