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

Social Work

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

N. Pagan, W. Mei, et al.

Dive into the innovative world of directed network formation on social media! This research, conducted by Nicolò Pagan, Wenjun Mei, Cheng Li, and Florian Dörfler, reveals how users follow fellow creators based on the quality of their content. Get ready to uncover a model that predicts user interactions follow Zipf's law, supported by fascinating Twitch data!

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Playback language: English
Abstract
This paper proposes a meritocratic model for directed network formation on social media platforms, where users follow others based on the quality of their user-generated content (UGC). The model predicts that the expected in-degree follows Zipf's law with respect to UGC quality ranking, a finding robust against recommendation systems. Empirical validation using Twitch data supports the model's predictions.
Publisher
Nature Communications
Published On
Jun 23, 2021
Authors
Nicolò Pagan, Wenjun Mei, Cheng Li, Florian Dörfler
Tags
social media
network formation
user-generated content
UGC quality
Zipf's law
Twitch data

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