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The relationship between offline partisan geographical segregation and online partisan segregation

Megan A. Brown, Tiago Ventura, Joshua A. Tucker, Jonathan Nagler

TL;DR

The study tackles whether online echo chambers on social media reflect offline partisan segregation by linking a massive offline voter-file dataset with Twitter networks. Using 1) offline isolation from 1,000 geographically proximate co-partisans and 2) online isolation from followers’ inferred partisanship via a Barbera-based ideology model, the authors directly compare online and offline sorting. They find offline partisan segregation is higher than online segregation for both parties, with Democrats more isolated than Republicans in both domains; online segregation can resemble offline sorting at the upper tail, and there is a positive correlation between online and offline isolation. These findings challenge the notion that social media alone drives echo chambers and highlight the importance of offline geographic context in shaping online political networks and attitudes.

Abstract

Social media is often blamed for the creation of echo chambers. However, these claims fail to consider the prevalence of offline echo chambers resulting from high levels of partisan segregation in the United States. Our article empirically assesses these online versus offline dynamics by linking a novel dataset of voters' offline partisan segregation extracted from publicly available voter files for 180 million US voters with their online network segregation on Twitter. We investigate offline and online partisan segregation using measures of geographical and network isolation of every matched voter-twitter user to their co-partisans online and offline. Our results show that while social media users tend to form politically homogeneous online networks, these levels of partisan sorting are significantly lower than those found in offline settings. Notably, Democrats are more isolated than Republicans in both settings, and only older Republicans exhibit higher online than offline segregation. Our results contribute to the emerging literature on political communication and the homophily of online networks, providing novel evidence on partisan sorting both online and offline.

The relationship between offline partisan geographical segregation and online partisan segregation

TL;DR

The study tackles whether online echo chambers on social media reflect offline partisan segregation by linking a massive offline voter-file dataset with Twitter networks. Using 1) offline isolation from 1,000 geographically proximate co-partisans and 2) online isolation from followers’ inferred partisanship via a Barbera-based ideology model, the authors directly compare online and offline sorting. They find offline partisan segregation is higher than online segregation for both parties, with Democrats more isolated than Republicans in both domains; online segregation can resemble offline sorting at the upper tail, and there is a positive correlation between online and offline isolation. These findings challenge the notion that social media alone drives echo chambers and highlight the importance of offline geographic context in shaping online political networks and attitudes.

Abstract

Social media is often blamed for the creation of echo chambers. However, these claims fail to consider the prevalence of offline echo chambers resulting from high levels of partisan segregation in the United States. Our article empirically assesses these online versus offline dynamics by linking a novel dataset of voters' offline partisan segregation extracted from publicly available voter files for 180 million US voters with their online network segregation on Twitter. We investigate offline and online partisan segregation using measures of geographical and network isolation of every matched voter-twitter user to their co-partisans online and offline. Our results show that while social media users tend to form politically homogeneous online networks, these levels of partisan sorting are significantly lower than those found in offline settings. Notably, Democrats are more isolated than Republicans in both settings, and only older Republicans exhibit higher online than offline segregation. Our results contribute to the emerging literature on political communication and the homophily of online networks, providing novel evidence on partisan sorting both online and offline.

Paper Structure

This paper contains 7 sections, 3 equations, 16 figures, 2 tables.

Table of Contents

  1. Survey Materials
  2. Comparing Online and Offline Isolation Across Urban and Rural Areas and Population Density
  3. Comparing Online and Offline Isolation Across Subgroups
  4. Robustness Checks: Offline Isolation Under Different Cut-offs
  5. Imputation for Voters' Partisan Identity
  6. Robustness Checks: Discrete Assignment of Partisanship
  7. Robustness Checks: Alternative Cutoffs for Online Isolation

Figures (16)

  • Figure 1: Correlation between ingroup isolation in an individual's neighborhood and ingroup isolation amongst their acquaintances (left) and their coworkers (right), separately for Democrats (blue) and Republicans (red).
  • Figure 1: Survey question for the ideological breakdown of an individual's acquaintences
  • Figure 2: Survey question for the ideological breakdown of an individual's neighbors
  • Figure 3: Relationship between Online and Offline Isolation. Democrats are shown in blue, and Republicans are in red. Each dot represents average online isolation over a hundred binned values of offline Isolation. Lines represent a smoothed non-linear function over the points
  • Figure 3: Survey question for the ideological breakdown of an individual's coworkers
  • ...and 11 more figures