Dataset Card for HumAID

Dataset Description
Dataset Structure
Dataset Creation
Considerations for Using the Data
Additional Information

Dataset Description

Homepage: https://crisisnlp.qcri.org/humaid_dataset
Repository: https://crisisnlp.qcri.org/data/humaid/humaid_data_all.zip
Paper: https://ojs.aaai.org/index.php/ICWSM/article/view/18116/17919

Dataset Summary

The HumAID Twitter dataset consists of several thousands of manually annotated tweets that has been collected during 19 major natural disaster events including earthquakes, hurricanes, wildfires, and floods, which happened from 2016 to 2019 across different parts of the World. The annotations in the provided datasets consists of following humanitarian categories. The dataset consists only english tweets and it is the largest dataset for crisis informatics so far. ** Humanitarian categories **

Caution and advice
Displaced people and evacuations
Dont know cant judge
Infrastructure and utility damage
Injured or dead people
Missing or found people
Not humanitarian
Other relevant information
Requests or urgent needs
Rescue volunteering or donation effort
Sympathy and support

Supported Tasks and Benchmark

The dataset can be used to train a model for multiclass tweet classification for disaster response. The benchmark results can be found in https://ojs.aaai.org/index.php/ICWSM/article/view/18116/17919.

Languages

English

Dataset Structure

Data Instances

{"tweet_text": "@RT_com: URGENT: Death toll in #Ecuador #quake rises to 233 \u2013 President #Correa #1 in #Pakistan", "class_label": "injured_or_dead_people"}

Data Fields

tweet_text: corresponds to the tweet text.
class_label: corresponds to a label assigned to a given tweet text.

Data Splits

Train
Development
Test

Dataset Creation

Source Data

Initial Data Collection and Normalization

Tweets has been collected during several disaster events.

Annotations

Annotation process

AMT has been used to annotate the dataset. Please check the paper for a more detail.

Datasets:

QCRI
/

HumAID-all