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  A Meritocratic Network Formation Model for the Rise of Social Media Influencers

Pagan, N., Mei, W., Li, C., & Dörfler, F. (2021). A Meritocratic Network Formation Model for the Rise of Social Media Influencers. Nature Communications, 6865.

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https://doi.org/10.1038/s41467-021-27089-8 (Publisher version)
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 Creators:
Pagan, Nicolò1, Author
Mei, Wenjun 1, Author
Li, Cheng2, Author           
Dörfler, Florian1, Author
Affiliations:
1External Organizations, ou_persistent22              
2MPI for Innovation and Competition, Max Planck Society, ou_2035292              

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 Abstract: Many of today’s most used online social networks such as Instagram, YouTube, Twitter, or Twitch are based on User-Generated Content (UGC). Thanks to the integrated search engines, users of these platforms can discover and follow their peers based on the UGC and its quality. Here, we propose an untouched meritocratic approach for directed network formation, inspired by empirical evidence on Twitter data: actors continuously search for the best UGC provider. We theoretically and numerically analyze the network equilibria properties under different meeting probabilities: while featuring common real-world networks properties, e.g., scaling law or small-world effect, our model predicts that the expected in-degree follows a Zipf’s law with respect to the quality ranking. Notably, the results are robust against the effect of recommendation systems mimicked through preferential attachment based meeting approaches. Our theoretical results are empirically validated against large data sets collected from Twitch, a fast-growing platform for online gamers.

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Language(s): eng - English
 Dates: 2021-11-30
 Publication Status: Published online
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Title: Nature Communications
  Abbreviation : Nat. Commun.
Source Genre: Journal
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Publ. Info: London : Nature Publishing Group
Pages: - Volume / Issue: - Sequence Number: 6865 Start / End Page: - Identifier: ISSN: 2041-1723
CoNE: https://pure.mpg.de/cone/journals/resource/2041-1723