Concentration without cumulative advantage: the distribution of news source attention in online communities
Abstract
Many attention markets exhibit stable patterns of concentration, where a few producers attract and sustain a far greater share of the audience than others. This inequality often follows patterns consistent with cumulative advantage, a process in which performance compounds over time. Attention to news sources online possesses these characteristics; however, online audiences also fragment across many disparate news producers. How do social media and recommender systems contribute to these attention dynamics? In this study, we examine two paradigmatic models: concentration driven by cumulative advantage and fragmentation driven by stochasticity. We evaluate these models against a large-scale empirical dataset of news source attention in the popular social media site Reddit. While we find high levels of attention concentration, we do not find the stable popularity over time that characterizes cumulative advantage. Rather, sources gain and lose popularity seemingly at random, aligning with a stochastic model. These results demonstrate the persistence of attention inequality, even in the absence of a strong driving mechanism. They also suggest that social media systems can undermine the accumulation of attention to the most prominent news sources. Digital attention markets striving for more equitable allocation require novel mechanisms of organizing and distributing information.
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A repository with more real stars tends to also get more real stars in the future, echoing the 'rich get richer' phenomenon.
“In other words, a repository with more real stars tends to also get more real stars in the future, echoing the 'rich get richer' phenomenon prevalent in social networks [52, 102].”
From Six Million (Suspected) Fake Stars on GitHub: A Growing Spiral of Popularity Contests, Spams, and Malware (2026) · cites this paper as [52]
The 'rich get richer' phenomenon is well-known and confirmed in online social media.
“the well-known 'rich get richer' phenomenon confirmed repeatedly in online social media and similar online contexts [52, 102]”
From Six Million (Suspected) Fake Stars on GitHub: A Growing Spiral of Popularity Contests, Spams, and Malware (2026) · cites this paper as [52]
Cites
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Salganik, M. J., Dodds, P. S., & Watts, D. J. (2006) · Science · doi:10.1126/science.1121066 · Cited by 2,219 · see citing works
Network Propaganda: Manipulation, Disinformation, and Radicalization in American Politics
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Self-citationProblematic Machine Behavior: A Systematic Literature Review of Algorithm Audits
Bandy, J. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3449148 · Cited by 193 · see citing works
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He, H., Yang, H., Burckhardt, P., Kapravelos, A., Vasilescu, B., & Kästner, C. (2026) · Proceedings of the 2026 IEEE/ACM 48th International Conference on Software Engineering · doi:10.1145/3744916.3764531 · Cited by 2 · see citing works
- Authors
- Hagar, N., & Shaw, A.
- Affiliations
- Northwestern University (US)
- Corresponding author
- Hagar, Nick
- Venue
- Journal of Communication
- Publisher
- Oxford University Press (OUP)
- Published
- 2022-09-22
- Volume
- 72
- Issue
- 6
- Pages
- 675-686
- ISSN
- 0021-9916 (ISSN-L)
- 1460-2466
- OpenAlex
- W4296676414
- Cited by
- 6
- References
- 5
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 1 · 2023: 2
- FWCI
- 0.38
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Communication (publishedVersion)
- Topics
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Physical Sciences › Computer Science › Computer Networks and Communications › Media and Digital Communication
- Social Sciences › Communication › Media Studies and Communication
- Keywords
- attention concentration, Matthew effect, social media, recommender systems, Reddit, attention dynamics, audience fragmentation
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