Twitter User-Hashtag Bipartite Network (Munmun)
A Twitter (user-hashtag interactions) dataset of 705,632 nodes and 1,890,661 edges, collected by Munmun De Choudhury et al. via Twitter API. Each record contains directed: False, weighted: True, signed: False, temporal: True. Bipartite temporal network linking Twitter users to hashtags they used, with Unix timestamps. Useful for studying hashtag adoption, information diffusion, and user interest modeling.. Suitable for hashtag analysis, bipartite network analysis, information diffusion.
Cite this dataset at
munmun-twitter-ex.echo.directory
Analytics
The full graph has 705,632 nodes; this view shows the 1,000-node sample the pipeline drew for display. Node size is centrality, colour is community.
Computed over the full corpus.
Record
- Catalog key
munmun-twitter-ex- Authors
- De Choudhury, Munmun; Lin, Yu-Ru; Sundaram, Hari; Candan, Kasim Selcuk; Xie, Lexing; Kelliher, Aisling
- Year
- 2010
- Source paper
- How Does the Data Sampling Strategy Impact the Discovery of Information Diffusion in Social Media?
- DOI / arXiv
- 10.1609/icwsm.v4i1.14024
- License
- CC BY-SA 2.0 Germany (as stated by KONECT) (LicenseRef-CC-BY-SA-2.0-DE)
- Records
- 705,632
- Nodes
- 705,632
- Edges
- 1,890,661
- Nodes are
- user / hashtag
- Edges are
- hashtag usage
- Attributes
- nodes have no attributes; edges have attributes
- Languages
- en
- Collected
- 2009 (2000s)
- Tasks
- From the graph: link prediction, community detection
- Region
- Global (inferred: the platform is used worldwide)
Provenance
- Originally published at
- https://konect.cc/networks/munmun_twitterex_ut/ unverified
- Hosted copy
- Mirrored on echo.directory on 2026-10-02, 27.4 MB across 1 files. Checksums in MANIFEST.json.
Citations
How Does the Data Sampling Strategy Impact the Discovery of Information Diffusion in Social Media?
Munmun De Choudhury, Y. Lin, Hari Sundaram, K. Candan, Lexing Xie
Journal Article · International Conference on Web and Social Media · 2010
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Nan Cao, Y. Lin et al. · IEEE Transactions on Visualization and Computer Graphics · 2012 · cited 233×
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}
}
@article{De_Choudhury_2010,
title = {How Does the Data Sampling Strategy Impact the Discovery of Information Diffusion in Social Media?},
volume = {4},
issn = {2162-3449},
url = {http://dx.doi.org/10.1609/icwsm.v4i1.14024},
doi = {10.1609/icwsm.v4i1.14024},
number = {1},
journal = {Proceedings of the International AAAI Conference on Web and Social Media},
publisher = {Association for the Advancement of Artificial Intelligence (AAAI)},
author = {De Choudhury, Munmun and Lin, Yu-Ru and Sundaram, Hari and Candan, Kasim Selcuk and Xie, Lexing and Kelliher, Aisling},
year = {2010},
month = May,
pages = {34–41}
} APA
Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory
De Choudhury, M., Lin, Y.-R., Sundaram, H., Candan, K. S., Xie, L., & Kelliher, A. (2010). Twitter User-Hashtag Bipartite Network (Munmun) [Data set]. https://doi.org/10.1609/icwsm.v4i1.14024
MLA
Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.
De Choudhury, Munmun, et al. Twitter User-Hashtag Bipartite Network (Munmun). 2010, doi.org/10.1609/icwsm.v4i1.14024.