Origraph：交互式网络管理
Origraph: Interactive Network Wrangling
摘要：
网络是思考许多数据集的自然方式。然而，网络所基于的数据很少以适合分析过程的形式收集，因此有必要创建和重塑网络。数据争论被广泛认为是数据分析管道的关键部分，但交互式网络争论在可视化研究社区中很少受到关注。在本文中，我们讨论了一组操作，是重要的争吵网络数据集，并介绍了一个可视化的数据争吵工具，Origraph，使分析师能够将这些操作应用到他们的数据集。关键操作包括从源数据（例如表）创建网络，通过引入新节点或边类来重塑网络，过滤节点或边，以及导出新节点或边属性。我们的工具Origraph使分析师能够执行这些操作，几乎没有编程，并立即可视化结果。Origraph提供了用于研究网络模型、网络样本以及节点和边属性的视图。此外，我们介绍了接口，旨在帮助分析师在指定合理的网络争吵操作的参数。我们证明了Origraph在两个用例中的实用性：首先，我们调查了电影业的性别偏见，然后是金钱对也门战争的政治支持的影响。
英文摘要：
Networks are a natural way of thinking about many datasets. The data on which a network is based, however, is rarely collected in a form that suits the analysis process, making it necessary to create and reshape networks. Data wrangling is widely acknowledged to be a critical part of the data analysis pipeline, yet interactive network wrangling has received little attention in the visualization research community. In this paper, we discuss a set of operations that are important for wrangling network datasets and introduce a visual data wrangling tool, Origraph, that enables analysts to apply these operations to their datasets. Key operations include creating a network from source data such as tables, reshaping a network by introducing new node or edge classes, filtering nodes or edges, and deriving new node or edge attributes. Our tool, Origraph, enables analysts to execute these operations with little to no programming, and to immediately visualize the results. Origraph provides views to investigate the network model, a sample of the network, and node and edge attributes. In addition, we introduce interfaces designed to aid analysts in specifying arguments for sensible network wrangling operations. We demonstrate the usefulness of Origraph in two Use Cases: first, we investigate gender bias in the film industry, and then the influence of money on the political support for the war in Yemen.
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。
