The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.
The Myth of Partisan Selective Exposure: A Portrait of the Online Political News Audience
Open accessAbstract
Many assume that in a digital environment with a wide range of ideologically tinged news outlets, partisan selective exposure to like-minded speech is pervasive and a primary cause of political polarization. Yet, partisan selective exposure research tends to stem from experimental or self-reported data, which limits the applicability of their findings in a high-choice media environment. We explore observed online audience behavior data to present a portrait of the actual online political news audience. We find that this audience frequently navigates to news sites from Facebook, and that it congregates among a few popular, well-known political news sites. We also find that political news sites comprise ideologically diverse audiences, and that they share audiences with nearly all smaller, more ideologically extreme outlets. Our results call into question the strength of the so-called red/blue divide in actual web use.
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Scheufele, D. A., & Krause, N. M. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1805871115 · Cited by 878
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McKay, S., & Tenove, C. (2021) · Political Research Quarterly · doi:10.1177/1065912920938143 · Cited by 378
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Algorithmic inference, political interest, and exposure to news and politics on Facebook
Thorson, K., Cotter, K., Medeiros, M., & Pak, C. (2021) · Information, Communication & Society · doi:10.1080/1369118x.2019.1642934 · Cited by 361
Metadata
- Authors
- Nelson, J. L., & Webster, J. G.
- Venue
- Social Media + Society
- Publisher
- SAGE Publications
- Published
- 2017-07
- Volume
- 3
- Issue
- 3
- ISSN
- 2056-3051 (ISSN-L)
- OpenAlex
- W2753353351
- Cited by
- 267
- References
- 61
- FWCI
- 43.33
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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