---
_id: '21916'
abstract:
- lang: eng
  text: 'Social network graphs are central to graph learning research, serving as
    standard benchmarks for algorithm evaluation. However, existing datasets focus
    mainly on mainstream social media platforms whose structures are shaped notably
    by algorithmic recommendations. This raises an important question: would alternative,
    decentralized social networks exhibit different properties? We address this by
    studying the Fediverse; a collection of decentralized social networks (such as
    Mastodon and Lemmy). These platforms differ fundamentally from for-profit social
    media, notably in decentralization and absence of recommendation algorithms, which
    may yield distinct graph structures. We introduce Fedivertex, a dataset of over
    400 graphs from seven decentralized networks, collected weekly over six months.
    The dataset, released with a companion Python package to facilitate its use, supports
    research on temporal and structural aspects of decentralized social networks.
    In particular, we benchmark applications to decentralized machine learning and
    community detection.'
article_processing_charge: No
author:
- first_name: Marc
  full_name: Damie, Marc
  last_name: Damie
- first_name: Edwige Audrey Lucienne
  full_name: Cyffers, Edwige Audrey Lucienne
  id: 20d4c299-977a-11ef-ae55-98b15ac64a57
  last_name: Cyffers
citation:
  ama: 'Damie M, Cyffers EAL. Fedivertex: A graph dataset based on decentralized Social
    Media. In: <i>2026 Proceedings of the ACM Web Conference 2026</i>. ACM; :8393-8396.
    doi:<a href="https://doi.org/10.1145/3774904.3792868">10.1145/3774904.3792868</a>'
  apa: 'Damie, M., &#38; Cyffers, E. A. L. (n.d.). Fedivertex: A graph dataset based
    on decentralized Social Media. In <i>2026 Proceedings of the ACM Web Conference
    2026</i> (pp. 8393–8396). Dubai: ACM. <a href="https://doi.org/10.1145/3774904.3792868">https://doi.org/10.1145/3774904.3792868</a>'
  chicago: 'Damie, Marc, and Edwige Audrey Lucienne Cyffers. “Fedivertex: A Graph
    Dataset Based on Decentralized Social Media.” In <i>2026 Proceedings of the ACM
    Web Conference 2026</i>, 8393–96. ACM, n.d. <a href="https://doi.org/10.1145/3774904.3792868">https://doi.org/10.1145/3774904.3792868</a>.'
  ieee: 'M. Damie and E. A. L. Cyffers, “Fedivertex: A graph dataset based on decentralized
    Social Media,” in <i>2026 Proceedings of the ACM Web Conference 2026</i>, Dubai,
    pp. 8393–8396.'
  ista: 'Damie M, Cyffers EAL. Fedivertex: A graph dataset based on decentralized
    Social Media. 2026 Proceedings of the ACM Web Conference 2026. WWW: Web Conference,
    8393–8396.'
  mla: 'Damie, Marc, and Edwige Audrey Lucienne Cyffers. “Fedivertex: A Graph Dataset
    Based on Decentralized Social Media.” <i>2026 Proceedings of the ACM Web Conference
    2026</i>, ACM, pp. 8393–96, doi:<a href="https://doi.org/10.1145/3774904.3792868">10.1145/3774904.3792868</a>.'
  short: M. Damie, E.A.L. Cyffers, in:, 2026 Proceedings of the ACM Web Conference
    2026, ACM, n.d., pp. 8393–8396.
conference:
  end_date: 2026-07-03
  location: Dubai
  name: 'WWW: Web Conference'
  start_date: 2026-06-29
date_created: 2026-05-24T22:01:32Z
date_published: 2026-04-12T00:00:00Z
date_updated: 2026-06-03T05:40:18Z
day: '12'
department:
- _id: ChLa
doi: 10.1145/3774904.3792868
language:
- iso: eng
month: '04'
oa_version: None
page: 8393-8396
publication: 2026 Proceedings of the ACM Web Conference 2026
publication_identifier:
  isbn:
  - '9798400723070'
publication_status: accepted
publisher: ACM
scopus_import: '1'
status: public
title: 'Fedivertex: A graph dataset based on decentralized Social Media'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2026'
...