“Rich-get-richer”? Platform attention and earnings inequality using Patreon earnings data

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ID: 322393
2026
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Abstract
Abstract Patreon allows content creators to monetize additional content from loyal fans. Because it offers minimal native distribution, Patreon earnings largely reflect creators’ popularity on their primary external platforms (Instagram, Twitch, YouTube, Twitter/X, Facebook, or “Patreon-only”), making them a useful proxy for platform-level algorithmic attention dynamics. Fitting power-law tails to Patreon earnings by primary platform affiliation, we find three key results. First, platforms exhibit “rich-get-richer” earnings dynamics (Barabási and Albert, 1999 Science, 286, 509–512), reflected in a Pareto exponent $\alpha \approx 2$, which is closer to concentrated capital income than labor income. Second, platforms with more concentrated earnings (lower $\alpha$) have lower mean and median earnings, and thus an eroded creator “middle class.” Third, across most platforms, $\alpha$ values decline and converge over time (based on three cross-sections: 2018, 2021, and 2024), meaning earnings become increasingly concentrated among top creators—consistent with algorithmic recommendations rising in importance. Algorithmic attention allocation is a plausible driver of these patterns, though platform-specific conversion rates and audience willingness to pay may be just as important.
Reference Key
openalex_W4416775758 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Ilan Strauss, Jangho Yang, Mariana Mazzucato
Journal industrial and corporate change
Year 2026
DOI
10.1093/icc/dtag044
URL
https://doi.org/10.1093/icc/dtag044
Keywords Keywords not found

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