Survey identifies visualization principles and gaps in information diffusion in networks, suggesting future directions.
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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Baumgartl et al. (2026) studied this question.
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