Mario L. Small’s research while affiliated with Columbia University and other places

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Publications (83)


The Avoidance of Strong Ties
  • Article

July 2024

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59 Reads

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1 Citation

American Sociological Review

Mario L. Small

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Kristina Brant

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Maleah Fekete

Theorists have proposed that a value of close friends and family—strong ties—is the ability to confide in them when facing difficult issues. But close relationships are complicated, and recent studies report that people sometimes avoid strong ties when facing personal issues. How common is such avoidance? The question speaks to theoretical debates over the nature of “closeness” and practical concerns over social isolation. We develop an approach and test it on new, nationally representative data. We find that, when facing personal difficulties, adult Americans are as likely to avoid as to talk to close friends and family. Most avoidance is not actively reflected on but passively enacted, and, contrary to common belief, is not limited to either specific network members or particular topics, depending instead on the conjunction of member and topic. Building on Simmel, we propose that a theory of the fundamental need to conceal and reveal helps account for the findings. We suggest that there is no more empirical justification for labeling strong ties as those who are trusted than for labeling them as those who are avoided. In turn, isolation might be less a matter of having no intimates than of having repeatedly to avoid them.


Fig. 2. Which urban places bring people "BCZ" depends on the city. BCZ scores for visits to POIs, for each category and city (gray circles). Median values across cities in color. Differences across POIs for the median city are small; differences within POIs across cities are large. Data for 2019, 100 largest US cities.
Fig. 3. The farther the POI, the more BCZ its neighborhood is-for the first ~10 km. Each line represents one city. Median value across cities in black. To reduce noise, bins in each city's top decile and distances greater than 50 km are dropped. For the first ~10 km, BCZ score increases with distance, leveling off on average thereafter. However, beyond ~10 km, heterogeneity across cities increases dramatically. For example, four cities with similar residential segregation levels-Long Beach (0.20), Buffalo (0.35), Dallas (0.35), and Louisville (0.28)-exhibit widely different BCZ scores beyond 10 km. Data for 2019, 100 largest US cities.
How people are exposed to neighborhoods racially different from their own
  • Article
  • Full-text available

July 2024

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58 Reads

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4 Citations

Proceedings of the National Academy of Sciences

In US cities, neighborhoods have long been racially segregated. However, people do not spend all their time in their neighborhoods, and the consequences of residential segregation may be tempered by the contact people have with other racial groups as they traverse the city daily. We examine the extent to which people’s regular travel throughout the city is to places “beyond their comfort zone” (BCZ), i.e., to neighborhoods of racial composition different from their own—and why. Based on travel patterns observed in more than 7.2 million devices in the 100 largest US cities, we find that the average trip is to a neighborhood less than half as racially different from the home neighborhood as it could have been given the city. Travel to grocery stores is least likely to be BCZ; travel to gyms and parks, most likely; however, differences are greatest across cities. For the first ~10 km people travel from home, neighborhoods become increasingly more BCZ for every km traveled; beyond that point, whether neighborhoods do so depends strongly on the city. Patterns are substantively similar before and after COVID-19. Our findings suggest that policies encouraging more 15-min travel—that is, to amenities closer to the home—may inadvertently discourage BCZ movement. In addition, promoting use of certain “third places” such as restaurants, bars, and gyms, may help temper the effects of residential segregation, though how much it might do so depends on city-specific conditions.

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Are Large-Scale Data From Private Companies Reliable? An Analysis of Machine-Generated Business Location Data in a Popular Dataset

April 2024

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11 Reads

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1 Citation

Large-scale data from private companies offer new opportunities to examine topics of scientific and social significance, such as racial inequality, partisan polarization, and activity-based segregation. However, because such data are often generated through automated processes, their accuracy and reliability for social science research remain unclear. The present study examines how quality issues in large-scale data from private companies can afflict the reporting of even ostensibly uncomplicated values. We assess the reliability with which an often-used device tracking data source, SafeGraph, sorted data it acquired on financial institutions into categories, such as banks and payday lenders, based on a standard classification system. We find major classification problems that vary by type of institution, and remarkably high rates of unidentified closures and duplicate records. We suggest that classification problems can affect research based on large-scale private data in four ways: detection, efficiency, validity, and bias. We discuss the implications of our findings, and list a set of problems researchers should consider when using large-scale data from companies.


A spatiotemporal decay model of human mobility when facing large-scale crises

August 2022

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243 Reads

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36 Citations

Proceedings of the National Academy of Sciences

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Yuanyuan Liu

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[...]

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A common feature of large-scale extreme events, such as pandemics, wildfires, and major storms is that, despite their differences in etiology and duration, they significantly change routine human movement patterns. Such changes, which can be major or minor in size and duration and which differ across contexts, affect both the consequences of the events and the ability of governments to mount effective responses. Based on naturally tracked, anonymized mobility behavior from over 90 million people in the United States, we document these mobility differences in space and over time in six large-scale crises, including wildfires, major tropical storms, winter freeze and pandemics. We introduce a model that effectively captures the high-dimensional heterogeneity in human mobility changes following large-scale extreme events. Across five different metrics and regardless of spatial resolution, the changes in human mobility behavior exhibit a consistent hyperbolic decline, a pattern we characterize as “spatiotemporal decay.” When applied to the case of COVID-19, our model also uncovers significant disparities in mobility changes—individuals from wealthy areas not only reduce their mobility at higher rates at the start of the pandemic but also maintain the change longer. Residents from lower-income regions show a faster and greater hyperbolic decay, which we suggest may help account for different COVID-19 rates. Our model represents a powerful tool to understand and forecast mobility patterns post emergency, and thus to help produce more effective responses.


Ethnography Upgraded

August 2022

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67 Reads

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13 Citations

Qualitative Sociology

The basic practice of ethnography has essentially remained unchanged in hundreds of years. How has online life changed things? I contrast two transformative inventions, the telephone and the internet, with respect to their impact on fieldwork. I argue that our current era has created entirely new constraints and opportunities for ethnographic research.


The data revolution in social science needs qualitative research

March 2022

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361 Reads

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42 Citations

Nature Human Behaviour

Although large-scale data are increasingly used to study human behaviour, researchers now recognize their limits for producing sound social science. Qualitative research can prevent some of these problems. Such methods can help to understand data quality, inform design and analysis decisions and guide interpretation of results.


AFIs are easier to get to as proportion minority in neighbourhood increases, regardless of whether neighbourhood is high or low poverty
a–c, Adjusted probability that an AFI establishment is faster to get to when travelling by foot (a), public transport (b) or car (c). All variables are set at the grand mean except that block group poverty is set at either 10% (for low) or 50% (for high), and racial/ethnic composition is set at 10%, 30%, 50%, 70% and 90% for the primary group. At each race/ethnicity level, the remaining population is equally split between the two other major racial/ethnic groups, except that 8% is always set to Asian and 2% to other (for example, if the primary group is 50% Black, the remainder is 20% white, 20% Latino, 8% Asian and 2% other). Unadjusted probability in dotted lines. Shaded area represents 95% confidence intervals. Number of observations: 21,852 for travel by car, 21,313 by public transport, 21,800 by foot. For coefficients, standard errors and odds ratios, see Supplementary Table 1a–c.
Source data
Could race differences in demand account for the pattern? Banks are still harder to get to in low-poverty, college-educated, minority homeowner neighbourhoods than high-poverty, low-education, white renter neighbourhoods
a–c, Adjusted probability that an AFI is faster to get to by foot (a), public transport (b) and car (c), based on model behind Fig. 1 (Supplementary Table 1a–c). All variables are set at the grand means except as follows: the bars on the left show the probability that an AFI is closer for neighbourhoods with 50% low income with unemployment at the 75th percentile (14% unemployed) of the total distribution, proportion college educated at the 25th percentile (11%) and proportion homeowner at the 25th percentile (25%); the bars on the right, for neighbourhoods with 10% low income with unemployment at the 25th percentile (5% unemployed), proportion college educated at the 75th percentile (47%) and proportion homeowner at the 75th percentile (71%). Error bars represent 95% confidence intervals. Number of observations: 21,852 for travel by car, 21,313 by public transport, 21,800 by foot.
Source data
Banks, alternative institutions and the spatial–temporal ecology of racial inequality in US cities

December 2021

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179 Reads

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40 Citations

Nature Human Behaviour

Research has made clear that neighbourhood conditions affect racial inequality. We examine how living in minority neighbourhoods affects ease of access to conventional banks versus alternative financial institutions (AFIs) such as check cashers and payday lenders, which some have called predatory. Based on more than 6 million queries, we compute the difference in the time required to walk, drive or take public transport to the nearest bank versus AFI from the middle of every block in each of 19 of the largest cities in the United States. The results suggest that race is strikingly more important than class: even after numerous conditions are accounted for, the AFI is more often closer than the bank in low-poverty racial/ethnic minority neighbourhoods than in high-poverty white ones. Results are driven not by the absence of banks but by the prevalence of AFIs in minority areas. Gaps appear too large to reflect simple differences in preferences.


What is “Qualitative” in Qualitative Research? Why the Answer Does not Matter but the Question is Important

December 2021

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444 Reads

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12 Citations

Qualitative Sociology

What is qualitative research? Aspers and Corte (2019) make a case for a definition that they believe captures what many qualitative researchers intuitively know. Although I agree with many of the authors’ points, I argue that the effort to identify what makes qualitative research qualitative requires there to be a clear single thing to define, and there is not; that confronting this fact forces their paper into a central contradiction; and that in spite of these and other problems, the paper succeeds in crystalizing questions that qualitative researchers must grapple with today. The authors’ most valuable contribution may be less its definition than the issues we are forced to clarify when concluding what we think about it.


15 - From Edward O. Laumann, Peter V. Marsden, and David Prensky, “The Boundary Specification Problem in Network Analysis”

October 2021

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14 Reads

In their influential chapter on the boundary specification problem in network analysis, Laumann, Marsden, and Prensky (1989) argued that social network data often do not mirror the true underlying social structures in which individuals are embedded. Rather, the validity of network data hinges on the alignment of network boundaries and the social system or social mechanisms being studied. For this reason, the process of determining which actors and relationships should be included in a network is among the most critical research design issues in social network analysis, requiring a tight alliance of theory and method. Here, we build on Laumann and coauthors’ insights, updating their review with contemporary examples, and extending their ideas to the personal network research design context. We begin by identifying characteristics of personal network research, such as boundary spanning, that introduce unique challenges and opportunities to the boundary definition issue. We then apply concepts from their typology, reviewing common strategies for establishing boundaries through name generators in the context of personal network research designs.


Citations (56)


... While this may be a reasonable assumption in some formal contexts where large organization can reallocate volunteers for a variety of tasks (e.g., from direct help to advocacy or fundraising), it makes less sense in an informal context where the need for help is constrained by the amount of people that one is aware of needing help. Furthermore, research has shown that actors avoid asking both weak and strong ties for support for a variety of reasons (Small, Brant, and Fekete 2024), implying that in the informal setting of personal or community networks, individuals may not have information on the actual level of need for help. Said differently, the needs in ego's network has to be somehow perceived by ego, either by perceiving alter's direct request for help or some sign displaying a need for help (for a model over difference ways personal networks are mobilized see Small 2021). ...

Reference:

Demands Networks and Volunteering
The Avoidance of Strong Ties
  • Citing Article
  • July 2024

American Sociological Review

... Fig. 1A shows the networks for each month, demonstrating its strong coverage in both urban and rural areas. While many studies using GPS location data are only able to impute demographic attributes using administrative statistics 44,45 , often aggregated to large areal units that make the estimates crude, the data that we leverage here allow us to decompose travel according to demographic attributes without resorting to imputation. ...

How people are exposed to neighborhoods racially different from their own

Proceedings of the National Academy of Sciences

... This is particularly the case to expand empirical testing to areas that may be more challenging to do so. While representativeness is a risk that will be considered in evaluation, 3 for hard-to-reach groups it is possible that augmenting primary data with synthetic data for these groups could aid representation and ensure these voices are more fully heard in the research (although see Lundberg et al. 2024, Small 2024). ...

The value of qualitative data in understanding failure in prediction
  • Citing Article
  • June 2024

Proceedings of the National Academy of Sciences

... Así, estas están mediadas por diferentes planos de la realidad. Uno de ellos tiene que ver con el contexto organizacional que estructura la vida cotidiana de las personas (Small, 2009). En el caso de las instituciones educativas, se trata de sus reglas, procedimientos, rutinas y jerarquías. ...

Unanticipated Gains: Origins of Network Inequality in Everyday Life
  • Citing Article
  • August 2009

... This also includes the reality that significant external shocks, like pandemics, can lead to sudden changes in mobility trends. This abrupt disruption in mobility trends can greatly diminish the precision of the forecasting models [110]. Thus, all the techniques we utilise in our strategy are focused on attaining the most accurate match to the existing data points. ...

A spatiotemporal decay model of human mobility when facing large-scale crises
  • Citing Article
  • August 2022

Proceedings of the National Academy of Sciences

... To analyze the retention of cultural impetus, this paper focuses on the media setting. The interaction between physical and virtual spaces calls for a re-evaluation of non-digital existence (Small, 2022). During the pandemic lockdown in Shanghai, interpersonal communication was limited within the WeChat group-virtual communities based in local neighborhoods. ...

Ethnography Upgraded

Qualitative Sociology

... Qualitative methods as conceptualised here refer to a diverse suite of methods for collecting non-numeric data, that could take the form of words, images or audio-visual recordings (Madil & Gough, 2008). Qualitative methods play an important role in the production of more in-depth and contextual research in social and behavioural sciences (Grigoropoulou & Small, 2022) yet open science discussions can often focus on quantitative data sharing. Given the personal nature of qualitative data, confidentiality and anonymity are major ethical concerns (Lamb et al, 2024). ...

The data revolution in social science needs qualitative research
  • Citing Article
  • March 2022

Nature Human Behaviour

... It is true, however, that to some extent this critique is qualified for those currents that are more similar to pragmatic approaches, as in these currents intertextuality, strategies and exchanges between discourses are the main units of analysis (Blommaert, 2005;Sullivan, 2012). Even so, there are certain possible or real discursive moves, specific types of meaning shift that operate among discourses, which have not received sufficient attention in the central aspects of literature on qualitative methodology (Small, 2021). ...

What is “Qualitative” in Qualitative Research? Why the Answer Does not Matter but the Question is Important

Qualitative Sociology

... In many cases, a primary purpose for conducting network analyses is to identify nodes that are particularly important (central) within that network. Numerous centrality measures have been defined (e.g., Bonacich, 1972Bonacich, , 1991Bonacich and Lloyd, 2001;Freeman, 1977Freeman, , 1979Freeman et al., 1991;Wasserman and Faust, 1994), and can be justified as indicating the importance or prominence of a node for directing and receiving different kinds of flows through a network (Borgatti, 2005;Butts, 2009). Centrality is a node-level property, but most measures of centrality can also be aggregated to define the centralization of the entire network (a graph-level measure of the concentration of centrality among the actors). ...

4 - From Elizabeth Bott, “Urban Families: Conjugal Roles and Social Networks”
  • Citing Article
  • October 2021