PHEME Rumour Dataset — sydneysiege
Twitter conversations around the Sydney Lindt café siege (December 2014), from the PHEME rumour dataset (Zubiaga, Liakata, Procter, Kochkina and colleagues; the complete release for rumour detection and veracity classification, figshare 6392078): 1,221 threads, each a source tweet and its replies, of which 522 were judged rumours by journalists and 699 not. Every rumour also carries its veracity as later established: 382 true, 86 false and 54 unverified. 23,996 tweets in all, with full tweet JSON. ECHO builds the reply network (22,775 reply links, each reply pointing to the tweet it answers) and labels each tweet with its thread's rumour status and, for source tweets, the veracity. Useful for rumour detection, rumour verification and modelling how conversations unfold. Annotations CC BY 4.0; Twitter retains the rights to tweet content. The archive PHEME_veracity.tar.bz2 is gzip-compressed despite its name (the name is the authors' own, kept so the checksum matches figshare): extract it with `tar xzf`.
Cite this dataset at
pheme-sydneysiege.echo.directory
Analytics
The full graph has 24,228 nodes; this view shows the 1,000-node sample the pipeline drew for display. Node size is centrality, colour is community.
Topic 0
Topic 1
Topic 2
Topic 3
Topic 4
Topic 5
Topic 6
Topic 7
Topic 8
- Non-rumour699 (57.2%)
- Rumour: true382 (31.3%)
- Rumour: false86 (7.0%)
- Rumour: unverified54 (4.4%)
Computed over the full corpus.
Record
- Catalog key
pheme-sydneysiege- Authors
- Kochkina, Elena; Liakata, Maria; Zubiaga, Arkaitz
- Year
- 2018
- Source paper
- All-in-one: Multi-task Learning for Rumour Verification
- License
- Creative Commons Attribution 4.0 International (CC BY 4.0); tweet content rights with Twitter (CC-BY-4.0)
- Records
- 23,996
- Nodes
- 24,228
- Edges
- 22,775 (directed)
- Nodes are
- tweet
- Edges are
- reply (reply -> tweet it answers)
- Attributes
- nodes have attributes; edges have no attributes
- Text corpus
- tweet text
- Languages
- en
- Collected
- 2014-12-14 to 2014-12-15 (2010s)
- Tasks
- Rumour & veracity classification (binary;
is_rumor, veracity) inferred
From the graph: link prediction, community detection - Region
- Global (inferred: the platform is used worldwide)
Provenance
- Originally published at
- https://figshare.com/articles/dataset/PHEME_dataset_for_Rumour_Detection_and_Veracity_C... link checked
- Hosted copy
- Mirrored on echo.directory on 2026-10-21, 44.4 MB across 2 files. Checksums in MANIFEST.json.
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{kochkina2018all,
title = {All-in-one: Multi-task Learning for Rumour Verification},
author = {Kochkina, Elena and Liakata, Maria and Zubiaga, Arkaitz},
booktitle = {Proceedings of the 27th International Conference on Computational Linguistics (COLING)},
pages = {3402--3413},
year = {2018},
url = {https://aclanthology.org/C18-1288}
} APA
Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory
Kochkina, E., Liakata, M., & Zubiaga, A. (2018). PHEME Rumour Dataset — sydneysiege [Data set]. https://pheme-sydneysiege.echo.directory/
MLA
Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.
Kochkina, Elena, et al. PHEME Rumour Dataset — sydneysiege. 2018, pheme-sydneysiege.echo.directory/.