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Super-Linear Growth and Rising Inequality in Online Social Communities: Insights from Reddit

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arxiv 2503.02661 v1 pith:Y34XID3E submitted 2025-03-04 physics.soc-ph

Super-Linear Growth and Rising Inequality in Online Social Communities: Insights from Reddit

classification physics.soc-ph
keywords subredditusersactivitycommentsnumberfoundredditsize
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We study the effect of the number of users on the activity of communities within the online content sharing and discussion platform Reddit, called subreddits. We found that comment activity on Reddit has a heavy-tailed distribution, where a large fraction of the comments are made by a small set of users. Furthermore, as subreddits grow in size, this behavior becomes stronger, with activity (measured by the comments made in a subreddit) becoming even more centralised in a (relatively) smaller core of users. We verify that these changes are not explained by finite size nor by sampling effects. Instead, we observe a systematic change of the distribution with subreddit size. To quantify the centralisation and inequality of activity in a subreddit, we used the Gini coefficient. We found that as subreddits grow in users, so does the Gini coefficient, seemingly as a natural effect of the scaling. We found that the excess number of comments (the total number of comments minus the total number of users) follows a power law with exponent 1.27. For each subreddit we considered a snapshot of one month of data, as a compromise between statistical relevance and change in the system's dynamics. We show results over the whole year 2021 (with each subreddit having twelve snapshots, at most), nevertheless all results were consistent when using a single month or different years.

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  1. Persistent Structural Inequality of Online Interactions Across Platforms

    cs.SI 2026-05 unverdicted novelty 5.0

    Inequality in online user engagement, quantified via KL-divergence, inverse coefficient of variation, and log-Gini on bipartite networks, remains stable over time across multiple platforms and interaction types.