Social capital II: determinants of economic connectedness

Abstract

Low levels of social interaction across class lines have generated widespread concern1–4 and are associated with worse outcomes, such as lower rates of upward income mobility4–7. Here we analyse the determinants of cross-class interaction using data from Facebook, building on the analysis in our companion paper7. We show that about half of the social disconnection across socioeconomic lines—measured as the difference in the share of high-socioeconomic status (SES) friends between people with low and high SES—is explained by differences in exposure to people with high SES in groups such as schools and religious organizations. The other half is explained by friending bias—the tendency for people with low SES to befriend people with high SES at lower rates even conditional on exposure. Friending bias is shaped by the structure of the groups in which people interact. For example, friending bias is higher in larger and more diverse groups and lower in religious organizations than in schools and workplaces. Distinguishing exposure from friending bias is helpful for identifying interventions to increase cross-SES friendships (economic connectedness). Using fluctuations in the share of students with high SES across high school cohorts, we show that increases in high-SES exposure lead low-SES people to form more friendships with high-SES people in schools that exhibit low levels of friending bias. Thus, socioeconomic integration can increase economic connectedness in communities in which friending bias is low. By contrast, when friending bias is high, increasing cross-SES interactions among existing members may be necessary to increase economic connectedness. To support such efforts, we release privacy-protected statistics on economic connectedness, exposure and friending bias for each ZIP (postal) code, high school and college in the United States at https://www.socialcapital.org.

Social capital I: measurement and associations with economic mobility

“…Doing so requires an understanding of the determinants of EC and potential interventions to increase it. We address these questions in the companion paper 9 , in which we study why economic connectedness varies with SES and how we can increase connectedness among individuals with low SES.…”

“…There is less homophily by parental SES during childhood than by own SES in adulthood, with a slope of 0.31 instead of 0.44. Much of this difference in slopes arises from the fact that SES in adulthood among friends from high school is more similar than their parents' SES, perhaps because children who befriend each other tend to follow similar trajectories 9 .…”

“…This geographical variation in connectedness is partially driven by differences in the share of high-SES individuals in an area and partly by differences in the rates at which low-SES individuals befriend high-SES individuals in their area. We decompose the relative contributions of these two factors, which we refer to as exposure and friending bias, in the companion paper 9 .…”

“…However, efforts to understand what types of social capital matter for these outcomes have been hindered by a lack of social network data. Here, in the first of a pair of papers 9 , we use data on 21 billion friendships from Facebook to study social capital. We measure and analyse three types of social capital by ZIP (postal) code in the United States: (1) connectedness between different types of people, such as those with low versus high socioeconomic status (SES); (2) social cohesion, such as the extent of cliques in friendship networks; and (3) civic engagement, such as rates of volunteering.…”

“…Here, we use data on the social networks of 72.2 million users of Facebook aged between 25 and 44 years to construct and publicly release (https://www.socialcapital.org) new measures of social capital for each ZIP code in the United States. In a companion paper 9 , we also release data on social capital for each high school (secondary school) and college (university). As in previous research using Facebook data [22][23][24][25][26] (Supplementary Information C.1), we use social network data as a proxy for real-world friendships rather than online interactions per se.…”