Social Connectedness and Education Disparities: The Role of Network Embedded Resources and Inequality Structures (Poster 7)

• In Event: Excellence in Education Research: Early Career Scholars and Their Work

Abstract

"It has been challenging to examine the effects of social networks on education inequality at scale due in part to the absence of high-quality social network measures that can be linked to large-scale student assessment data. Utilizing online friendship data from Facebook, this study develops three sets of measures of network characteristics at the county level, including network geographic and socioeconomic heterophily, network-embedded socioeconomic resources, and network-embedded inequality structures. These measures are then linked to county-level data on student academic performance and disparities from the Stanford Education Data Archive (SEDA) to examine three research questions: 1) Are counties with similar levels of socioeconomic and education resources more connected, thus reinforcing inequality of resource distribution? 2) How are county network heterophily associated with county student performance and disparities across socioeconomic and racial groups? 3) How are county network embedded resources and inequality structures associated with student performance and disparities? Findings show that counties with similar levels of socioeconomic resources and student performance are more likely to be connected. Countries with more out-of-county friendship connections show higher performance among the socioeconomically advantaged students but not disadvantaged students, leading to a larger performance gap based on student SES. Moreover, findings reveal a race-specific effect of county network SES: counties with a higher level of network-embedded Black SES show higher performance among Black students and a smaller White-Black performance gap, while the network-embedded White SES shows an opposite effect. Results point to new initiatives to address education inequalities through social network resources and platforms.
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Author

• Ran Liu, University of Wisconsin - Madison
  Presenting Author