Wu Yanhong, Pitipornvivat Naveen, Zhao Jian, Yang Sixiao, Huang Guowei, Qu Huamin
IEEE Trans Vis Comput Graph. 2016 Jan;22(1):260-9. doi: 10.1109/TVCG.2015.2468151.
Ego-network, which represents relationships between a specific individual, i.e., the ego, and people connected to it, i.e., alters, is a critical target to study in social network analysis. Evolutionary patterns of ego-networks along time provide huge insights to many domains such as sociology, anthropology, and psychology. However, the analysis of dynamic ego-networks remains challenging due to its complicated time-varying graph structures, for example: alters come and leave, ties grow stronger and fade away, and alter communities merge and split. Most of the existing dynamic graph visualization techniques mainly focus on topological changes of the entire network, which is not adequate for egocentric analytical tasks. In this paper, we present egoSlider, a visual analysis system for exploring and comparing dynamic ego-networks. egoSlider provides a holistic picture of the data through multiple interactively coordinated views, revealing ego-network evolutionary patterns at three different layers: a macroscopic level for summarizing the entire ego-network data, a mesoscopic level for overviewing specific individuals' ego-network evolutions, and a microscopic level for displaying detailed temporal information of egos and their alters. We demonstrate the effectiveness of egoSlider with a usage scenario with the DBLP publication records. Also, a controlled user study indicates that in general egoSlider outperforms a baseline visualization of dynamic networks for completing egocentric analytical tasks.
自我网络代表了特定个体（即自我）与与之相连的人（即他我）之间的关系，是社交网络分析中一个关键的研究对象。自我网络随时间的演化模式为社会学、人类学和心理学等许多领域提供了深刻见解。然而，由于其复杂的时变图结构，动态自我网络的分析仍然具有挑战性，例如：他我来来去去，关系变强或变淡，以及他我社区合并和分裂。现有的大多数动态图可视化技术主要关注整个网络的拓扑变化，这对于以自我为中心的分析任务来说是不够的。在本文中，我们提出了egoSlider，一种用于探索和比较动态自我网络的可视化分析系统。egoSlider通过多个交互式协调视图提供数据的整体视图，在三个不同层面揭示自我网络的演化模式：宏观层面用于总结整个自我网络数据，介观层面用于概述特定个体的自我网络演化，微观层面用于显示自我及其他我的详细时间信息。我们通过DBLP出版记录的使用场景展示了egoSlider的有效性。此外，一项对照用户研究表明，总体而言，egoSlider在完成以自我为中心的分析任务方面优于动态网络的基线可视化。
