DiPD: Disruptive Event Prediction Dataset
A Twitter dataset of 263,555 tweets with binary event labels (14,129 disruptive events, 248,499 non-events) related to Bitcoin and cryptocurrency markets, collected by Mehta et al. via Twitter API, 2021. Each record contains tweet text, binary event/non-event label, follower count, location, username, Bitcoin price at time of tweet, and retweet count. one of few datasets explicitly linking social media content to financial market disruption events, with synchronized Bitcoin price data enabling direct study of social signal → market movement relationships. Suitable for event detection, financial market prediction from social media, cryptocurrency sentiment analysis, and disruptive event classification.
Cite this dataset at
dipd.echo.directory
Analytics
Topic 0
Topic 1
Topic 2
Topic 3
Topic 4
Topic 5
Topic 6
Topic 7
Topic 8
Topic 9
Topic 10
Topic 11
Sampled: text metrics from 50K of 263.6K records; topic model from 20K.
Record
- Catalog key
dipd- Authors
- Soni, Sanskar; Mehta, Dev; Vishwanath, Vinush; Seetha, Aditi; Chouhan, Satyendra Singh
- Year
- 2021
- Source paper
- DiPD: Disruptive event Prediction Dataset from Twitter
- DOI / arXiv
- 10.48550/arXiv.2111.15629
- License
- Unknown — GitHub repository, check repo for terms
- Records
- 263,555
- Text corpus
- tweet text
- Languages
- en
- Collected
- 2021 (2020s)
- Region
- Global (inferred: the platform is used worldwide)
Provenance
- Originally published at
- https://github.com/devmehta01/DiPD link checked
- Hosted copy
- Mirrored on echo.directory on 2026-10-09, 104.7 MB across 5 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}
}
@misc{https://doi.org/10.48550/arxiv.2111.15629,
doi = {10.48550/ARXIV.2111.15629},
url = {https://arxiv.org/abs/2111.15629},
author = {Soni, Sanskar and Mehta, Dev and Vishwanath, Vinush and Seetha, Aditi and Chouhan, Satyendra Singh},
keywords = {Social and Information Networks (cs.SI), Computation and Language (cs.CL), Information Retrieval (cs.IR), Machine Learning (cs.LG), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {DiPD: Disruptive event Prediction Dataset from Twitter},
publisher = {arXiv},
year = {2021},
copyright = {Creative Commons Attribution Non Commercial No Derivatives 4.0 International}
} APA
Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory
Soni, S., Mehta, D., Vishwanath, V., Seetha, A., & Chouhan, S. S. (2021). DiPD: Disruptive Event Prediction Dataset [Data set]. https://doi.org/10.48550/arXiv.2111.15629
MLA
Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.
Soni, Sanskar, et al. DiPD: Disruptive Event Prediction Dataset. 2021, doi.org/10.48550/arXiv.2111.15629.