NetworkNarratives: Data Tours for Visual Network Exploration and Analysis

ACM CHI 2023


This paper introduces semi-automatic data tours to aid the exploration of complex networks. Exploring networks requires significant effort and expertise and can be time-consuming and challenging. Distinct from guidance and recommender systems for visual analytics, we provide a set of goal-oriented tours for network overview, ego-network analysis, community exploration, and other tasks. Based on interviews with five network analysts, we developed a user interface (NetworkNarratives) and 10 example tours. The interface allows analysts to navigate an interactive slideshow featuring facts about the network using visualizations and textual annotations. On each slide, an analyst can freely explore the network and specify nodes, links, or subgraphs as seed elements for follow-up tours. Two studies, comprising eight expert and 14 novice analysts, show that data tours reduce exploration effort, support learning about network exploration, and can aid the dissemination of analysis results. NetworkNarratives is available online, together with detailed illustrations for each tour.




The authors would like to thank the experts and participants for their help in the project, as well as the anonymous reviewers for their valuable comments. This work is partially supported by Hong Kong RGC GRF Grant (No. 16210321), a grant from MSRA, EPSRC (Project EP/V010662/1, EP/T517884/1), and NSFC (No. 62202105).