Show simple item record

dc.contributor.author
Pagan, Nicolo
dc.contributor.author
Mei, Wenjun
dc.contributor.author
Cheng, Li
dc.contributor.author
Li, Cheng
dc.contributor.author
Dörfler, Florian
dc.date.accessioned
2021-12-01T14:44:09Z
dc.date.available
2021-12-01T13:20:02Z
dc.date.available
2021-12-01T13:20:33Z
dc.date.available
2021-12-01T14:44:09Z
dc.date.issued
2021
dc.identifier.issn
2041-1723
dc.identifier.other
10.1038/s41467-021-27089-8
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/518016
dc.identifier.doi
10.3929/ethz-b-000518016
dc.description.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.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Nature
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.title
A meritocratic network formation model for the rise of social media influencers
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2021-11-30
ethz.journal.title
Nature Communications
ethz.journal.volume
12
en_US
ethz.journal.issue
1
en_US
ethz.journal.abbreviated
Nat Commun
ethz.pages.start
6865
en_US
ethz.size
12 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
London
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02650 - Institut für Automatik / Automatic Control Laboratory::09478 - Dörfler, Florian / Dörfler, Florian
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02650 - Institut für Automatik / Automatic Control Laboratory::09478 - Dörfler, Florian / Dörfler, Florian
en_US
ethz.date.deposited
2021-12-01T13:20:08Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2021-12-01T14:44:21Z
ethz.rosetta.lastUpdated
2022-03-29T16:21:46Z
ethz.rosetta.versionExported
true
ethz.COinS
ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.atitle=A%20meritocratic%20network%20formation%20model%20for%20the%20rise%20of%20social%20media%20influencers&rft.jtitle=Nature%20Communications&rft.date=2021&rft.volume=12&rft.issue=1&rft.spage=6865&rft.issn=2041-1723&rft.au=Pagan,%20Nicolo&Mei,%20Wenjun&Cheng,%20Li&Li,%20Cheng&D%C3%B6rfler,%20Florian&rft.genre=article&rft_id=info:doi/10.1038/s41467-021-27089-8&
 Search print copy at ETH Library

Files in this item

Thumbnail

Publication type

Show simple item record