metadata

license: cc-by-nc-sa-4.0
task_categories:
  - text-classification
language:
  - en
tags:
  - Disaster
  - Crisis Informatics
pretty_name: >-
  HumAID: Human-Annotated Disaster Incidents Data from Twitter -- Event type
  dataset
size_categories:
  - 10K<n<100K
dataset_info:
  - config_name: flood
    splits:
      - name: train
        num_examples: 7815
      - name: dev
        num_examples: 1137
      - name: test
        num_examples: 2214
  - config_name: fire
    splits:
      - name: train
        num_examples: 7792
      - name: dev
        num_examples: 1134
      - name: test
        num_examples: 2207
  - config_name: earthquake
    splits:
      - name: train
        num_examples: 6250
      - name: dev
        num_examples: 909
      - name: test
        num_examples: 1773
configs:
  - config_name: flood
    data_files:
      - split: train
        path: flood/train.json
      - split: dev
        path: flood/dev.json
      - split: test
        path: flood/test.json
  - config_name: fire
    data_files:
      - split: train
        path: fire/train.json
      - split: dev
        path: fire/dev.json
      - split: test
        path: fire/test.json
  - config_name: earthquake
    data_files:
      - split: train
        path: earthquake/train.json
      - split: dev
        path: earthquake/dev.json
      - split: test
        path: earthquake/test.json
  - config_name: hurricane
    data_files:
      - split: train
        path: hurricane/train.json
      - split: dev
        path: hurricane/dev.json
      - split: test
        path: hurricane/test.json

HumAID: Human-Annotated Disaster Incidents Data from Twitter

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

The resulting annotated dataset consists of 11 labels.

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.

Dataset is also released with event-wise and JSON objects for further research. Full set of the dataset can be found in https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/A7NVF7

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

Tweets has been collected during several disaster events.

Annotations

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

Who are the annotators?

crowdsourced

Licensing Information

cc-by-nc-4.0

Citation Information

@inproceedings{humaid2020,
Author = {Firoj Alam, Umair Qazi, Muhammad Imran, Ferda Ofli},
booktitle={Proceedings of the Fifteenth International AAAI Conference on Web and Social Media},
series={ICWSM~'21},
Keywords = {Social Media, Crisis Computing, Tweet Text Classification, Disaster Response},
Title = {HumAID: Human-Annotated Disaster Incidents Data from Twitter},
Year = {2021},
publisher={AAAI},
address={Online},
}