Zipf's Law across social media

Michael Cameron

Working Papers in Economics from University of Waikato

Abstract: Zipf's Law describes an empirical regularity that appears across many human and physical domains, and states that ranked data exhibits a power law distribution. Although there are various extant studies illustrating power law relationships using social media data, we significantly extend these previous studies by looking at eight popular online social media networks: (1) Twitter; (2) YouTube; (3) Instagram; (4) Twitch; (5) DLive; (6) TikTok; (7) Daily Motion; and (8) Facebook. Specifically, we test whether the distribution of connections (followers, subscribers, or likes) follows a power law distribution for the top 5000 members of each social network. We find strong evidence that a power law relationship exists for every one of the social networks that we study, although this relationship breaks down for users at the top of the connections distribution. Despite the finding of a power law relationship for all of these social networks, the degree of inequality in social media connections differs substantially across the different networks, with the highest degree of inequality in DLive, and the lowest degree in TikTok and YouTube.

Keywords: Social media; Zipf's Law; Power Law; Pareto distribution (search for similar items in EconPapers)
JEL-codes: D85 L86 (search for similar items in EconPapers)
Pages: 16 pages
Date: 2022-03-11
New Economics Papers: this item is included in nep-hme, nep-net and nep-pay
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Persistent link: https://EconPapers.repec.org/RePEc:wai:econwp:22/07

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