Network Narratives: Data Tours for Visual Network Exploration and Analysis

被引:1
|
作者
Li, Wenchao [1 ]
Schottler, Sarah [2 ]
Scott-Brown, James [2 ]
Wang, Yun [3 ]
Chen, Siming [4 ]
Qu, Huamin [1 ]
Bach, Benjamin [2 ]
机构
[1] Hong Kong Univ Sci & Technol, Hong Kong, Peoples R China
[2] Univ Edinburgh, Edinburgh, Midlothian, Scotland
[3] Microsoft Res Asia, Beijing, Peoples R China
[4] Fudan Univ, Shanghai, Peoples R China
来源
PROCEEDINGS OF THE 2023 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI 2023) | 2023年
基金
英国工程与自然科学研究理事会;
关键词
Guided exploration; network visualization; VISUALIZATION; GUIDANCE; NAVIGATION; DESIGN;
D O I
10.1145/3544548.3581452
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页数:15
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