Analyzing change in network polarization
Abstract
The growing influence of social media in an era of media fragmentation has amplified concerns of political polarization. Yet relatively few studies have analyzed polarization in user networks over time. This study therefore examines change in network polarization on Twitter during a highly contested general election. Using Twitter’s REST API, user networks of 3000 randomly selected followers of well-known partisan and entertainment-oriented accounts were recorded 17 times in the 7 months leading up to the 2016 general election. Results suggest that partisan users form highly partisan networks on Twitter, while moderate, or less engaged, users continue to mostly avoid politics.
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Partisan networks were exponentially growing and becoming more politically homogenous during U.S. elections.
“Kearney (2019) showed that partisan networks were exponentially growing and becoming more politically homogenous during U.S. elections.”
From When debates break apart: discursive polarization as a multi-dimensional divergence emerging in and through communication (2023) · cites this paper as Kearney (2019)
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References 79 · Cited by 39
- Authors
- Kearney, M. W.
- Affiliations
- University of Missouri (US)
- Corresponding author
- Kearney, Michael Wayne
- Venue
- New Media & Society
- Publisher
- SAGE Publications
- Published
- 2019-01-10
- Volume
- 21
- Issue
- 6
- Pages
- 1380-1402
- ISSN
- 1461-4448 (ISSN-L)
- 1461-7315
- OpenAlex
- W2909508774
- Cited by
- 39
- References
- 79
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 3 · 2023: 6 · 2022: 14 · 2021: 3 · 2020: 5 · 2019: 2
- FWCI
- 12.72
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- New Media & Society (publishedVersion)
- Topics
- Social Sciences › Communication › Social Media and Politics
- Social Sciences › Sociology and Political Science › Media Influence and Politics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Keywords
- political polarization, Twitter, social media, media fragmentation, user engagement
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