Since the inception of the discipline, sociologists have sought to understand the role of neighborhoods and communities in organizing everyday urban life. From demographic investigation of the changing nature of racial and socioeconomic segregation to the rich ethnographic accounts of urban social organization, investigation of urban spatial variation has animated sociological inquiry. Critical findings have emerged from this work, including the durable nature of segregation in U.S. cities and the role of social processes, such as collective trust in understanding the consequences of neighborhood poverty for health and wellbeing.
Despite considerable progress, our understanding of urban neighborhood life has been hampered by two key obstacles—the absence of information on where people actually spend time and their in-the-moment experience of the spaces they routinely encounter. Until recently, researchers have lacked data on everyday mobility—where people go and how much time they spend at urban locations. These basic data allow sociologists to assess the relevance of home neighborhoods in the lives of residents. How much time do people spend outside their home in their neighborhood? Does this vary for children, adolescents, and adults? If people spend significant amounts of time outside their home neighborhoods, an overemphasis on the conditions of residential neighborhoods may miss important experiences beyond these settings. Among the recently available data resources allowing us to address these questions are large-scale, commercially available smartphone data tracking the movements of millions of individuals—sometimes over significant periods of time.
Such data sources emerged as a critical source of information on the mobility patterns of individuals during the COVID-19 pandemic. Epidemiologists and public health authorities were desperately in need of information on exposure patterns and the geography of disease transmission risk. Smartphone GPS data allowed for early observation of spatial variation in social distancing practices. Beyond the pandemic, sociologists have made use of geotagged smartphone and social media data to track mobility across neighborhoods of differing racial composition and estimate how often people are likely to encounter individuals of differing race/ethnicity in the course of their everyday routines.
As important as these new data are for insight into urban behavior, they present a number of limitations. First, they lack linked information on the demographic and other social characteristics of device users. Research on interracial encounters during daily routines, for instance, must infer the race/ethnicity of the device user based on compositional characteristics of the home neighborhood—a strategy likely to introduce error, particularly for those residing in integrated neighborhoods. Second, typically, these data do not include information on precise, pointwise locations due to concerns about privacy and identifiability.
Research Data Paints a Richer Portrait
Sociologists have a long history of groundbreaking research employing social surveys that provide rich information on individuals and families including, but also beyond, their demographic characteristics. A fruitful extension of this tradition of data collection combines survey information with data collection through smartphone devices. These data may include GPS information on the daily mobility and travel paths of individuals, short surveys administered to study participants asking about locations, and other sensor information drawn from smartphone (or other linked) devices. Because of the process of garnering consent from study participants, researchers are positioned to make explicit what types of data will be collected and how these data will be shared and secured. Consequently, investigator-initiated original data collection efforts involving mobile tracking often have access to far more detailed individual device user information and more precise location information than is afforded by large-scale commercial data resources.
My colleagues and I have been engaged in a 15-year effort to integrate smartphone devices into more standard social survey data collection efforts. This project—the Adolescent Health and Development in Context (AHDC) study, focused on the Columbus, OH, metro area—has yielded insights into daily mobility that enhance, and sometimes challenge, existing urban research. For instance, although research on the spatial contexts of youth development has focused largely on residential neighborhood environments, our team finds that youth spend relatively little time in their residential census tract (an area typically capturing about 4,000 people and the most commonly used operationalization of “neighborhood”). Youth ages 11 to 17 spend about 6 percent of waking-time (roughly an hour of a 16-hour day) outside home in their residential tract. In contrast, youth spend about 60 percent of waking-time at home, and 34 percent in outside-home-neighborhood spaces. These data point to the potentially significant role of areas beyond the home neighborhood in the daily lives of urban youth.
Two additional findings shed light on the complexity of everyday mobility. First, regardless of where Black youth live, they disproportionately spend time in economically and socially disadvantaged areas compared to white youth, largely due to the high likelihood of social ties to residents of racially segregated neighborhoods. Our team’s research demonstrates substantial racial disparities in exposure to area-level violence, for instance, even for white and Black youth who reside in the same neighborhood, underscoring the potential for incorrect estimates of violence and other adverse exposures in the absence of rich mobility data.
Second, and related, non-home-neighborhood settings may differ substantially from the home neighborhood. For instance, AHDC data indicate that Black youth residing in high-proportion (greater than 70 percent) Black neighborhoods spend more non-home time in high-proportion white tracts than high-proportion Black tracts. This process is driven by the concentration of urban organizational resources (e.g., schools and businesses) in more affluent and typically whiter neighborhoods. Consequently, focusing only on the residential neighborhood may miss not just a substantial proportion of the average day, but time spent in areas that differ significantly from the home neighborhood space.
Learning from Experience Sampling/Ecological Momentary Assessment
This brings us to the second information source sorely needed to advance research on urban communities—data on the experience of different urban spaces in the course of daily routine activities. Many theories of urban influence on health and development assume that neighborhoods and other everyday settings shape experiences (behaviors, perceptions, social interactions) that are relevant for longer-term outcomes. Widespread use of smartphones has allowed researchers to administer brief, phone-based mini-surveys—sometimes referred to as experience sampling or ecological momentary assessment (EMA)—to capture these real-time experiences directly. These data allow us to ask whether, for instance, youth are more likely to experience stress when spending time in economically disadvantaged or higher violence neighborhoods, as is often speculated. Moreover, random administration of EMAs pick up experiences across the range of neighborhood types to which youth are exposed. For instance, we might ask how Black youth who spend time in whiter, and typically more affluent neighborhoods experience these contexts.
Again, AHDC data shed light on these questions. When asked on an EMA whether they agree or disagree that they are at a safe location in the moment, both Black and white youth are less likely to report safety when in higher violence neighborhoods. However, Black youth also report lower levels of safety when spending time in high-proportion white neighborhoods (a finding not observed for white youth, unsurprisingly). In turn, average reports of safety over the course of a week are positively associated with elevated cortisol levels—a stress hormone, chronically high levels of which are linked with longer-term adverse health outcomes. Similarly, although white youth report more positive mood on EMAs when in groups of youth, we only observe this association for Black youth when they are in less affluent contexts. We reported these findings in work that we recently presented at the ASA 2025 Annual Meeting in Chicago in a session on “Space and Place.” When in more affluent, typically whiter neighborhoods, individual Black youth in groups of Black youth report lower positive affect—particularly when in a group including a Black male. The perception that Black males draw negative scrutiny in more affluent settings may limit the extent to which Black youth experience group-based activities positively when in advantaged neighborhoods.
The ability to track mobility and record real-time responses to environments calls attention to the complexity of everyday mobility and experience for racialized youth and leads us to ask different questions regarding the neighborhood origins of ongoing racial disparities in health and well-being. Rich and large-scale data on individual perceptions of social environments can also be aggregated to the area level in order to understand variations across space in average perceptions of phenomena such as violence, safety, and community trust.
Toward a Balanced Approach to Data Collection
Although a fruitful source of information on cities, administrative, social media and other large-scale data sources draw us away from the experiential dynamics illuminated by EMA. Echoing recent calls, we argue that a balanced approach to data collection would involve a significant role for social surveys on neighborhoods and other routine locations as well as smartphone and potentially other sensor-based data. This would enrich—and in some cases correct—findings drawn from administrative and commercial data. The obstacles to this strategy are also significant. Integrating mobility and EMA data into conventional social surveys requires resources, and the current research funding environment does not inspire confidence. Yet, when considered from the standpoint of pressing questions facing contemporary society, the case for investing in original data collections of the kind proposed here becomes clearer.
A possible starting point lies in the process of preparing for future pandemics. National, systematically collected mobility data with demographic and other social information attached would provide a far richer resource for understanding potential disease transmission patterns than is currently available. Such data would help illuminate the social factors that (profoundly) shape social distancing willingness and capacity. Beyond this headline need are the myriad additional sociological questions that might be addressed with nationally representative data on mobility: What are the everyday social and spatial contexts of loneliness? What kinds of public spaces generate positive (or conflictual) social interactions? How do adolescent boys’ and girls’ experiences of everyday safety vary across settings? Emerging advances in smartphone-based research point to a future in which they serve as an essential tool to better understand the social world in motion.