SpreadLine：可视化自我中心动态影响
SpreadLine: Visualizing Egocentric Dynamic Influence
AI总结：
本文提出 SpreadLine 可视化框架，基于故事线和地铁图隐喻从强度、功能、结构和内容四个方面探索自我中心网络动态关系，并通过案例与可用性研究验证其有效性。
摘要：
自我中心网络通常被可视化为节点-链接图，描绘实体（节点）与其他实体之间的复杂关系（链接）动态。然而，常见的分析任务是多元的，涵盖四个关键方面的交互：强度、功能、结构和内容。当前的节点-链接可视化设计可能存在不足，仅狭隘地关注某些方面，而忽略了自我中心网络的整体动态特性。为了弥合这一差距，我们引入了 SpreadLine，这是一种新颖的可视化框架，旨在从微观层面实现这四个方面的自我中心网络视觉探索。利用故事线可视化的直观吸引力，SpreadLine 采用基于故事线的设计来表示实体及其不断演变的关系。我们进一步在布局中编码必要的拓扑信息，并在地铁图隐喻中浓缩上下文信息，从而提供一种更具吸引力和有效的方式来探索基于时间和属性的信息。为了指导我们的工作，通过对相关文献的全面回顾，我们提炼出一个任务分类法，以解决自我中心网络探索特有的分析需求。认识到用户分析需求的多样性，SpreadLine 提供可定制的编码，使用户能够根据任务定制框架。我们通过三个不同的真实世界案例研究（疾病监测、社交媒体趋势和学术生涯演变）以及一项可用性研究，证明了 SpreadLine 的有效性和通用性。
英文摘要：
Egocentric networks, often visualized as node-link diagrams, portray the complex relationship (link) dynamics between an entity (node) and others. However, common analytics tasks are multifaceted, encompassing interactions among four key aspects: strength, function, structure, and content. Current node-link visualization designs may fall short, focusing narrowly on certain aspects and neglecting the holistic, dynamic nature of egocentric networks. To bridge this gap, we introduce SpreadLine, a novel visualization framework designed to enable the visual exploration of egocentric networks from these four aspects at the microscopic level. Leveraging the intuitive appeal of storyline visualizations, SpreadLine adopts a storyline-based design to represent entities and their evolving relationships. We further encode essential topological information in the layout and condense the contextual information in a metro map metaphor, allowing for a more engaging and effective way to explore temporal and attribute-based information. To guide our work, with a thorough review of pertinent literature, we have distilled a task taxonomy that addresses the analytical needs specific to egocentric network exploration. Acknowledging the diverse analytical requirements of users, SpreadLine offers customizable encodings to enable users to tailor the framework for their tasks. We demonstrate the efficacy and general applicability of SpreadLine through three diverse real-world case studies (disease surveillance, social media trends, and academic career evolution) and a usability study.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
