A meritocratic network formation model for the rise of social media influencers.

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

SUBMITTER: Pagan N 

PROVIDER: S-EPMC8633025 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature