"Rich-Get-Richer"? Analyzing Content Creator Earnings Across Large Social Media Platforms

Ilan Strauss, Jangho Yang and Mariana Mazzucato

Papers from arXiv.org

Abstract: This paper examines whether monthly content creator earnings follow a power law distribution, driven by compounding 'rich-get-richer' dynamics (Barabasi and Albert 1999). Patreon creator earnings data for 2018, 2021, and 2024 for Instagram, Twitch, YouTube, Twitter, Facebook, and Patreon exhibit a power law exponent around $\alpha = 2$. This suggests that algorithmic systems generate unequalizing returns closer to highly concentrated capital income and wealth, rather than labor income. Platforms governed by powerful and compounding recommendation systems, such as Instagram and YouTube, exhibit both a stronger power law relation (lower $\alpha$) and lower mean, median, and interquartile earnings, indicating algorithms that disproportionately favor top earners at the expense of a 'middle class' of creators. In contrast, Twitter and Patreon have a more moderate $\alpha$, with less earnings inequality and higher middle class earnings. Policies which incentivize the algorithmic promotion of longer-tail content (to explore more and exploit less) may help creator ecosystems become more equitable and sustainable.

Date: 2025-09
References: Add references at CitEc
Citations:

Downloads: (external link)
http://arxiv.org/pdf/2509.26523 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2509.26523

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().