HumAID: Humanitarian Crisis Dataset (Cumulative)
A Twitter dataset of 76,484 tweets across 19 events, 10 humanitarian categories, collected by Alam et al. for 19 natural disaster events (2016-2019). Each record contains tweet text, humanitarian category label, event name, train/dev/test split. Largest publicly available human-annotated crisis dataset with 76,484 tweets across 19 events. Suitable for crisis informatics, humanitarian response, text classification, social media analysis.
Cite this dataset at
humaid-cumulative.echo.directory
Analytics
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Sampled: text metrics from 50K of 76.5K records; topic model from 20K.
Record
- Catalog key
humaid-cumulative- Authors
- Alam, Firoj; Ofli, Ferda; Imran, Muhammad
- Year
- 2020
- Source paper
- HumAID: A Human-Annotated Dataset for Disaster Response
- DOI / arXiv
- 10.1609/icwsm.v15i1.18116
- License
- Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) (CC-BY-NC-SA-4.0)
- Records
- 76,484
- Text corpus
- tweet text
- Languages
- en
- Collected
- 2016-2019 (2010s)
- Region
- Global (inferred: the platform is used worldwide)
Provenance
- Originally published at
- https://github.com/ChenBeici/SocialED_datasets/tree/main/raw_data/HumAID link checked
- Hosted copy
- Mirrored on echo.directory on 2026-10-02, 14.0 MB across 57 files. Checksums in MANIFEST.json.
Citations
HumAID: Human-Annotated Disaster Incidents Data from Twitter with Deep Learning Benchmarks
Firoj Alam, U. Qazi, Muhammad Imran, Ferda Ofli
Journal Article · International Conference on Web and Social Media · 2021
Cited by
- CrisisBench: Benchmarking Crisis-related Social Media Datasets for Humanitarian Information Processing
Firoj Alam, Hassan Sajjad et al. · International Conference on Web and Social Media · 2021 · cited 119× - Location Reference Recognition from Texts: A Survey and Comparison
Xuke Hu, Zhi-Yong Zhou et al. · ACM Computing Surveys · 2022 · cited 96× - MEDIC: a multi-task learning dataset for disaster image classification
Firoj Alam, Tanvirul Alam et al. · Neural computing & applications (Print) · 2021 · cited 95× - Zero- and Few-Shot Prompting with LLMs: A Comparative Study with Fine-tuned Models for Bangla Sentiment Analysis
Md Arid Hasan, Shudipta Das et al. · International Conference on Language Resources and Evaluation · 2023 · cited 76× - Extraction and analysis of natural disaster-related VGI from social media: review, opportunities and challenges
Yu Feng, Xiao Huang et al. · International Journal of Geographical Information Science · 2022 · cited 62×
Show all 10
- Harnessing Large Language Models for Disaster Management: A Survey
Zhen-Yu Lei, Yu-Shun Dong et al. · Annual Meeting of the Association for Computational Linguistics · 2025 · cited 55× - Harnessing prompt-based large language models for disaster monitoring and automated reporting from social media feedback
Riccardo Cantini, Cristian Cosentino et al. · Online Soc. Networks Media · 2025 · cited 42× - JointMatch: A Unified Approach for Diverse and Collaborative Pseudo-Labeling to Semi-Supervised Text Classification
Henry Peng Zou, Cornelia Caragea · Conference on Empirical Methods in Natural Language Processing · 2023 · cited 36× - We Know You Are Living in Bali: Location Prediction of Twitter Users Using BERT Language Model
Lihardo Faisal Simanjuntak, Rahmad Mahendra et al. · Big Data and Cognitive Computing · 2022 · cited 35× - GazPNE2: A General Place Name Extractor for Microblogs Fusing Gazetteers and Pretrained Transformer Models
Xuke Hu, Zhi-Yong Zhou et al. · IEEE Internet of Things Journal · 2022 · cited 34×
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{alam2020humaid,
author = {Alam, Firoj and Ofli, Ferda and Imran, Muhammad},
title = {HumAID: A Human-Annotated Dataset for Disaster Response},
year = {2020},
booktitle = {Proceedings of the 17th International Conference on Information Systems for Crisis Response and Management},
series = {ISCRAM '20}
} APA
Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory
Alam, F., Ofli, F., & Imran, M. (2020). HumAID: Humanitarian Crisis Dataset (Cumulative) [Data set]. https://doi.org/10.1609/icwsm.v15i1.18116
MLA
Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.
Alam, Firoj, et al. HumAID: Humanitarian Crisis Dataset (Cumulative). 2020, doi.org/10.1609/icwsm.v15i1.18116.