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Abstract
Emerging research suggests that the extent to which activity spaces—the collection of an individual’s routine activity locations—overlap provides important information about the functioning of a city and its neighborhoods. To study patterns of overlapping activity spaces, we draw on the notion of an ecological network, a type of two-mode network with the two modes being individuals and the geographic locations where individuals perform routine activities. We describe a method for detecting “ecological communities” within these networks based on shared activity locations among individuals. Specifically, we identify latent activity pattern profiles, which, for each community, summarize its members’ probability distribution of going to each location, and community assignment vectors, which, for each individual, summarize his or her probability distribution of belonging to each community. Using data from the Adolescent Health and Development in Context Study, we employ latent Dirichlet allocation to identify activity pattern profiles and communities. We then explore differences across neighborhoods in the strength and within-neighborhood consistency of community assignment. We hypothesize that these aspects of the neighborhood structure of ecological community membership capture meaningful dimensions of neighborhood functioning likely to covary with economic and racial composition. We discuss the implications of a focus on ecological communities for the conduct of “neighborhood effects” research more broadly.
最新研究显示, 活动空间（个人所有日常活动位置的集合）重叠的程度可提供关于城市和邻里运转情况的重要信息。为了研究活动空间重叠的模式, 我们借鉴了生态网络的概念。这个网络包含了两个模式：个人模式, 个人进行日常活动地理位置模式。我们阐述了一种根据个体共享活动位置检测这些网络中 “生态社区” 的方法。在这个过程中, 我们针对潜在活动模式进行了概况描述。针对每个社区, 我们总结了社区成员去往每个位置的概率分布和社区分配矢量；针对个人, 我们总结了个人在每个社区中归属分布的可能性。利用《青少年健康与发展背景研究》(Adolescent Health and Development in Context Study)的数据, 我们采用潜在狄利克雷分配模型识别活动模式的概况和社区, 然后探索社区分配强度和街道社区内一致性方面的差异。我们假设生态社区成员团体中的这种邻里结构, 能够体现可能随经济和种族构共变的街道社区运作方式。我们还探讨了关注生态社区对开展“邻里效应”研究的意义。
La investigación de avanzada sugiere que la amplitud con la que se traslapan los espacios de actividad––la colección de localizaciones de la actividad rutinaria de un individuo––suministra información de importancia acerca del funcionamiento de una ciudad y de sus vecindarios. Para estudiar los patrones de traslape de los espacios de actividad, nos basamos en la noción de una cadena ecológica, un tipo de red de doble modalidad en la que los dos modos son los individuos y las localizaciones geográficas donde éstos llevan a cabo sus actividades rutinarias. Describimos un método para detectar “comunidades ecológicas” dentro de estas redes con base en localizaciones de actividad compartidas entre individuos. Específicamente, identificamos los perfiles de patrones de actividad latentes, los cuales, por cada comunidad, resumen la distribución de probabilidades de sus miembros de ir a cada punto locacional, y los vectores de asignación comunitarios que, por cada individuo, resumen su distribución de probabilidad de pertenencia para cada comunidad. Usando datos del Estudio de Salud y Desarrollo Adolescente en Contexto, empleamos la asignación latente de Dirichlet para identificar los perfiles de patrones de actividad y las comunidades. Enseguida exploramos las diferencias de fortaleza a través de los vecindarios y la consistencia de las tareas comunitarias dentro de los vecindarios. Proponemos la hipótesis de que estos aspectos de la estructura de membresía comunitaria ecológica captan las dimensiones significativas del funcionamiento vecinal, propenso a covariar con la composición económica y racial. Discutimos las implicaciones de enfocarse en las comunidades ecológicas por conducir la investigación de “los efectos vecinales” de modo más amplio.
Supplemental Material
Appendix A consists of figures for each of the top ten most visited block groups. Appendix B consists of figures for each of the eighteen detected communities.
This article contains Supplemental data available on the publisher’s Web site.
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Notes on contributors
Wenna Xi
WENNA XI was a PhD student in Biostatistics at The Ohio State University when the research was conducted and is currently a Postdoctoral Associate in the Department of Healthcare Policy and Research at Weill Cornell Medicine, New York, NY 10065. E-mail: [email protected]. Her research interests include social network analysis, spatial statistics, Bayesian modeling, and methods of integrating and analyzing complex structured data.
Catherine A. Calder
CATHERINE A. CALDER is Professor of Statistics and Data Sciences at the University of Texas at Austin, Austin, TX 78712. E-mail: [email protected]. She was on the faculty of The Ohio State University and served as Co-Director of the Mathematical Biosciences Institute at the time of this study. Her research interests include spatial statistics, Bayesian modeling and computation, and statistical network analysis, with an emphasis on applications in the social, environmental, and health sciences.
Christopher R. Browning
CHRISTOPHER R. BROWNING is Distinguished Professor of Sociology and an affiliate of the Institute for Population Research at The Ohio State University, Columbus, OH 43210. E-mail: [email protected]. His research focuses on neighborhood and activity space influences on health and development, emphasizing the causes and consequences of social processes such as routine activity patterns, ecological networks, and collective efficacy.