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The social integration of a city depends on the extent to which people from different neighborhoods have the opportunity to interact with one another, but most prior work has not developed formal ways of conceptualizing and measuring this kind of connectedness. In this article, we develop original, network-based measures of what we call “structural connectedness” based on the everyday travel of people across neighborhoods. Our principal index captures the extent to which residents in each neighborhood of a city travel to all other neighborhoods in equal proportion. Our secondary index captures the extent to which travels within a city are concentrated in a handful of receiving neighborhoods. We illustrate the value of our indices for the 50 largest American cities based on hundreds of millions of geotagged tweets over 18 months. We uncover important features of major American cities, including the extent to which their connectedness depends on a few neighborhood hubs, and the fact that in several cities, contact between some neighborhoods is all but nonexistent. We also show that cities with greater population densities, more cosmopolitanism, and less racial segregation have higher levels of structural connectedness. Our indices can be applied to data at any spatial scale, and our measures pave the way for more powerful and precise analyses of structural connectedness and its effects across a broad array of social phenomena.

Since the early 2000s, the proliferation of cameras, whether in mobile phones or CCTV, led to a sharp increase in visual recordings of human behavior. This vast pool of data enables new approaches to analyzing situational dynamics. Application is both qualitative and quantitative and ranges widely in fields such as sociology, psychology, criminology, and education. Despite the potential and numerous applications of this approach, a consolidated methodological frame does not exist. This article draws on various fields of study to outline such a frame, what we call video data analysis (VDA). We discuss VDA’s research agenda, methodological forebears, and applications, introduce an analytic tool kit, and discuss criteria for validity. We aim to establish VDA as a methodological frame and an interdisciplinary analytic approach, thereby enhancing efficiency and comparability of studies, and communication among disciplines that employ VDA. This article can serve as a point of reference for current and future practitioners, reviewers, and interested readers.

This study investigates the degree to which community can be found in Dutch neighbourhoods and attempts to explain why there is more community in some neighbourhoods than in others. We apply a perspective on community which assumes that people create communities with the expectation to realize some important well-being goals. Conditions that account for the creation of a local community are specified, i.e. the opportunity, ease, and motivation to do so. These conditions are realized when (i) neighbourhoods have more meeting places; (ii) neighbours are, given their resources and interests, motivated to invest in local relationships; (iii) neighbours have few relations outside of the neighbourhood, and (iv) neighbours are mutually interdependent. Data from the Survey of Social Networks of the Dutch on 1,007 respondents in 168 neighbourhoods are used. Results show that there is a sizeable amount of community in Dutch neighbourhoods and that all the four conditions contribute to the explanation, while interdependencies among neighbours have the strongest impact on the creation of community.