Moving window and hot spot detection analyses are statistical methods used to analyze point patterns within a given area. Such methods have been used to successfully detect clusters of point events such as car thefts or incidences of cancer. Yet, these methods do not account for the connections between individual events, such as social ties within a neighborhood. This paper presents two GIS methods, EdgeScan and NDScan, for capturing areas with high and low levels of local social connections. Both methods are moving window processes that count the number of edges and network density, respectively, in a given focal area (window area). The focal window attaches resultant EdgeScan and NDScan statistics to nodes at the center of the focal window area. We implement these methods on a case study of 1960s connections between members of the Mafia in New York City. We use various definitions of a focal neighborhood including Euclidean, Manhattan and K Nearest Neighbor (KNN) definitions. We find that KNN tends to overstate the values of local networks, and that there is more variation in outcome values for nodes on the periphery of the study area. We find that, location-wise, EdgeScan and NDScan hot spots differ from traditional spatial hot spots in the study area. These methods can be extended to future studies that detect local triads and motifs, which can capture the local network structure in more detail.

中文翻译：

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空间社交网络 (SSN) 热点检测：非平面网络的扫描方法

移动窗口和热点检测分析是用于分析给定区域内的点模式的统计方法。此类方法已被用于成功检测点事件集群，例如汽车盗窃或癌症发病率。然而，这些方法并没有考虑到单个事件之间的联系，例如社区内的社会联系。本文介绍了两种 GIS 方法 EdgeScan 和 NDScan，用于捕获具有高和低水平本地社会联系的区域。这两种方法都是移动窗口过程，分别计算给定焦点区域（窗口区域）中的边缘数量和网络密度。焦点窗口将生成的 EdgeScan 和 NDScan 统计数据附加到焦点窗口区域中心的节点。我们在 1960 年代纽约市黑手党成员之间联系的案例研究中实施了这些方法。我们使用焦点邻域的各种定义，包括欧几里得、曼哈顿和 K 最近邻 (KNN) 定义。我们发现 KNN 倾向于夸大局部网络的值，并且研究区域外围节点的结果值变化更大。我们发现，就位置而言，EdgeScan 和 NDScan 热点与研究区域中的传统空间热点不同。这些方法可以扩展到检测局部三合会和图案的未来研究，可以更详细地捕获局部网络结构。我们发现 KNN 倾向于夸大局部网络的值，并且研究区域外围节点的结果值变化更大。我们发现，就位置而言，EdgeScan 和 NDScan 热点与研究区域中的传统空间热点不同。这些方法可以扩展到检测局部三元组和图案的未来研究，可以更详细地捕获局部网络结构。我们发现 KNN 倾向于夸大局部网络的值，并且研究区域外围节点的结果值变化更大。我们发现，就位置而言，EdgeScan 和 NDScan 热点与研究区域中的传统空间热点不同。这些方法可以扩展到检测局部三合会和图案的未来研究，可以更详细地捕获局部网络结构。