TPVis: A Temporal Path Visualization System for Intuitive Understanding of Information Diffusion Inside Temporal Networks
Jincheol Oh, Haifa L. Gaza, Eunsol Gang, Jaewook Byun · IEEE Access · 2025
Analyses of temporal graphs provide valuable insights into temporal networks via two analytical approaches (temporal evolution and temporal information diffusion). The former explains how a network evolves over time; the latter shows how information diffuses over a temporal network. Various temporal graph visualization techniques could be applied to boost the comprehension of temporal evolution and make decisions more accurate. However, there are problems in the case of temporal information diffusion that worsen the understanding: visual misalignment, visual disconnection, and time-constraint violation. In the paper, we propose a novel system that supports intuitive understanding of temporal information diffusion, TPVis. TPVis directly computes and visualizes temporal paths into a timeline-based layout, which is computationally challenging while this approach is more scalable than existing approaches in terms of the number of required events and valid times. We present an efficient incremental algorithm to compute temporal paths and design the procedure for path-to- tree conversion to alleviate the problems above, which is shown in our case studies.