HumAID-events

# 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},
}
```

# HumAID：来自Twitter的人工标注灾害数据集（Human-Annotated Disaster Incidents Data from Twitter）

## 数据集说明

- **主页：** https://crisisnlp.qcri.org/humaid_dataset
- **代码仓库：** https://crisisnlp.qcri.org/data/humaid/humaid_data_all.zip
- **论文：** https://ojs.aaai.org/index.php/ICWSM/article/view/18116/17919

### 数据集概述
本HumAID Twitter数据集包含数千条人工标注的推文，采集自2016年至2019年间全球范围内发生的19起重大自然灾害事件，涵盖地震、飓风、山火与洪水等灾害类型。本数据集的标注涵盖以下人道主义相关类别。该数据集仅包含英文推文，是目前危机信息学领域规模最大的公开数据集。

**人道主义类别**
- 警示与建议
- 流离失所人员与疏散行动
- 无法判定
- 基础设施与公共设施损毁
- 人员伤亡
- 人员失联与寻获
- 非人道主义相关
- 其他相关信息
- 请求或紧急需求
- 救援、志愿行动或捐赠活动
- 慰问与支持

最终标注完成的数据集共包含11个类别标签。

### 支持任务与基准测试
本数据集可用于训练面向灾害响应的多分类推文分类模型，相关基准测试结果可参阅上述论文链接。本数据集同时按事件维度发布，并提供JSON格式数据以供后续研究使用。完整数据集可在哈佛大学数据verse平台获取：https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/A7NVF7

### 语言
英语

## 数据集结构

### 数据实例
json
{
"tweet_text": "@RT_com: URGENT: Death toll in #Ecuador #quake rises to 233 – President #Correa #1 in #Pakistan",
"class_label": "injured_or_dead_people"
}

### 数据字段
* tweet_text：对应推文文本内容
* class_label：对应给定推文文本所分配的类别标签

### 数据划分
* 训练集
* 开发集
* 测试集

## 数据集构建
推文采集自多起自然灾害事件。

### 标注信息
本数据集采用AMT（Amazon Mechanical Turk，亚马逊机械 Turk）进行标注，详细标注流程请参阅相关论文。

#### 标注人员来源
- 众包标注者

### 许可证信息
- CC BY-NC 4.0

### 引用信息
bibtex
@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},
}