FediData: Multi-Modal Fediverse (Mastodon) Dataset
MastodonA Mastodon (Fediverse) dataset of 725,282 posts from 64,345 users across 493 instances, collected by Gao et al. for CIKM 2025. Each record contains post text, image URLs, and following/follower edge relationships with a 12,548-user manual bot/human/unclassifiable label subset. The dataset is notable for its multilingual corpus with 92.8% image attachment rate and 4-way bot classification scheme across a decentralized federated network. Intended for research into bot detection, decentralized social network structure, and multi-modal content analysis.
Cite this dataset at
fedidata.echo.directory
Analytics
The full graph has 64,345 nodes; this view shows the 1,000-node sample the pipeline drew for display. Node size is centrality, colour is community.
Topic 0
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Show all 14 topics
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Computed over the full corpus.
Record
- Catalog key
fedidata- Authors
- Gao, Min; Du, Haoran; Wen, Wen; Duan, Qiang; Wang, Xin; Chen, Yang
- Year
- 2025
- Source paper
- FediData: A Comprehensive Multi-Modal Fediverse Dataset from Mastodon
- DOI / arXiv
- 10.1145/3746252.3761634
- License
- Creative Commons Attribution 4.0 International (CC BY 4.0) (CC-BY-4.0)
- Records
- 725,282
- Nodes
- 64,345
- Edges
- 1,948,528 (directed)
- Nodes are
- user
- Edges are
- follow
- Attributes
- nodes have attributes; edges have attributes
- Text corpus
- post text
- Languages
- de, en, es, fr, ja, nl
- Collected
- 2023-2024 (2020s)
- Tasks
- Bot detection inferred
From the graph: link prediction, community detection - Region
- Global (inferred: the platform is used worldwide)
Provenance
- Originally published at
- https://zenodo.org/records/15621244 link checked
Citations
FediData: A Comprehensive Multi-Modal Fediverse Dataset from Mastodon
Min Gao, Hao-Ran Du, Wen Wen, Qiang Duan, Xin Wang
Journal Article · International Conference on Information and Knowledge Management · 2025
Cited by
- FediScan: Collaborative Social Bot Detection in the Fediverse
Min Gao, Wen Wen et al. · The Web Conference · 2026 · cited 1× - Multi-Strategy Improvement and Comparative Research on Data-Driven Social Network Construction in Edge-Deficient Scenarios for Social Bot Account Detection
Junjie Wang, Minghu Tang · Inf. · 2026 · cited 0× - Adaptive Multi-Level Graph Compression with Structural Preservation for Large-Scale Network
Linyan Zhu, Zi-Pei Fan et al. · 2026 5th International Symposium on Computer Applications and Information Technology (ISCAIT) · 2026 · cited 0×
Citation data from Semantic Scholar, retrieved 2026-10-19.
How to cite
BibTeX
@misc{echo2026,
title = {ECHO: Exploratory Compendium of Humanity Online},
author = {Switzer, Braden and Zafarani, Reza},
year = {2026},
url = {https://echo.directory},
note = {Syracuse University}
}
@inproceedings{gao2025fedidata,
title = {{FediData: A Comprehensive Multi-Modal Fediverse Dataset from Mastodon}},
author = {Min Gao and Haoran Du and Wen Wen and Qiang Duan and Xin Wang and Yang Chen},
year = {2025},
booktitle = {Proceedings of the 34th ACM International Conference on Information and Knowledge Management (CIKM'25)},
pages = {6372--6376}
} APA
Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory
Gao, M., Du, H., Wen, W., Duan, Q., Wang, X., & Chen, Y. (2025). FediData: Multi-Modal Fediverse (Mastodon) Dataset [Data set]. https://doi.org/10.1145/3746252.3761634
MLA
Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.
Gao, Min, et al. FediData: Multi-Modal Fediverse (Mastodon) Dataset. 2025, doi.org/10.1145/3746252.3761634.