News by Popular Demand: Ideological Congruence, Issue Salience, and Media Reputation in News Sharing
Open accessAbstract
Social media news sharing has become a central subject of scholarly research in communication studies. To test current theories, it is of an utmost importance to estimate the meaningful parameters of news sharing behavior from observational data. In this article, we retrieve measures of ideological congruence, issue salience, and media reputation to explain news sharing in social media. We describe how the proposed statistical model connects to different strands of the news sharing literature. We then exemplify the usefulness of the model with an analysis of the relationship between ideological congruence and issue salience. Results show that if ideology and salience correlate with each other, the preferences of ideologues (i.e., users who give higher weight to ideological congruence) will be overrepresented in observational data. This will result in the heightened perceptions of polarization. We test the performance of the model using data from Brazil, Argentina, and the United States.
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In the identified studies, nodes often represent users and edges denote interactions between users and interaction of users with content such as posts or hyperlinks to news pages.
“In the identified studies, nodes often represent users and edges denote interactions between users and interaction of users with content such as posts or hyperlinks to news pages (e.g., [108]).”
From A systematic review of echo chamber research: comparative analysis of conceptualizations, operationalizations, and varying outcomes (2025) · cites this paper as [108]
The Louvain algorithm, Leiden algorithm, random walk modelling, greedy algorithms, latent space models, flow stability or hierarchical clustering algorithms are used in most cases of the included studies to detect communities in the bipartite graph.
“The Louvain algorithm, 10 Leiden algorithm 11 (e.g., [99]), random walk modelling (e.g., [108, 127]), greedy algorithms (e.g., [94]), latent space models 12 (e.g., [8,100]), flow stability (e.g., [146]) or hierarchical clustering algorithms (e.g., [90]) are used in most cases of the included studies to detect communities in the bipartite graph.13”
From A systematic review of echo chamber research: comparative analysis of conceptualizations, operationalizations, and varying outcomes (2025) · cites this paper as [108]
Cites
Filter Bubbles, Echo Chambers, and Online News Consumption
Flaxman, S., Goel, S., & Rao, J. M. (2016) · Public Opinion Quarterly · doi:10.1093/poq/nfw006 · Cited by 1,992 · see citing works
Uncivil Agreement: How Politics Became Our Identity
Mason, L. (2018) · doi:10.7208/chicago/9780226524689.001.0001 · Cited by 1,985 · cited 1× · see citing works
“A broad literature on affective polarization has shown that intense ideologues are also unconditionally more motivated to participate in politics and in social media (Barberá 2020; Guess 2021; Huddy et al. 2015; Mason 2018).”
BackgroundBirds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data
Barberá, P. (2015) · Political Analysis · doi:10.1093/pan/mpu011 · Cited by 982 · cited 1× · see citing works
“This assumption is accepted practice in the emerging literature on social media preferences (Barberá 2015; Bond and Messing 2015; Conover et al. 2011).”
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Algorithm-mediated social learning in online social networks
Brady, W. J., Jackson, J. C., Lindström, B., & Crockett, M. J. (2023) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2023.06.008 · Cited by 132 · see citing works
Hartmann, D., Wang, S. M., Pohlmann, L., & Berendt, B. (2025) · Journal of Computational Social Science · doi:10.1007/s42001-025-00381-z · Cited by 59 · see citing works
- Authors
- Aruguete, N., Calvo, E., & Ventura, T.
- Affiliations
- Departamento de Ciencias Sociales, Universidad Nacional de Quilmes, UNQ
- University of Maryland, College Park (US)
- Corresponding author
- Ventura, Tiago
- Venue
- The International Journal of Press/Politics
- Publisher
- SAGE Publications
- Published
- 2021-12-10
- Volume
- 28
- Issue
- 3
- Pages
- 558-579
- ISSN
- 1040-1620 (ISSN-L)
- 1940-1612
- 1940-1620
- OpenAlex
- W4200292994
- Cited by
- 15
- References
- 3
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 2 · 2023: 2 · 2022: 4
- FWCI
- 2.54
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- The International Journal of Press/Politics (publishedVersion)
- Conicet (submittedVersion, cc-by-nc-sa)
- Topics
- Social Sciences › Sociology and Political Science › Media Influence and Politics
- Social Sciences › Communication › Social Media and Politics
- Social Sciences › Communication › Media Studies and Communication
- Keywords
- news sharing, social media, ideological congruence, issue salience, media reputation, perceived polarization, user preferences
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