HumAID-event-type

# 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：人工标注的Twitter灾害事件数据集（Human-Annotated Disaster Incidents Data from Twitter）

## 数据集说明
- **数据集主页**：https://crisisnlp.qcri.org/humaid_dataset
- **代码仓库**：https://crisisnlp.qcri.org/data/humaid/humaid_data_all.zip
- **相关论文**：https://ojs.aaai.org/index.php/ICWSM/article/view/18116/17919

### 数据集概览
HumAID Twitter数据集包含数千条经人工标注的推文，这些推文采集自2016年至2019年间全球范围内19起重大自然灾害事件，涵盖地震、飓风、野火与洪水等灾害类型。本数据集提供的标注涵盖以下人道主义相关类别，且仅包含英文推文，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情况
- 无法判断
- 基础设施与公用设施损毁
- 人员伤亡
- 人员失踪或被找到
- 非人道主义相关内容
- 其他相关信息
- 请求或紧急需求
- 救援、志愿或捐赠行动
- 慰问与支持
最终的标注数据集共包含11个分类标签。

### 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考https://ojs.aaai.org/index.php/ICWSM/article/view/18116/17919。
本数据集同时按事件维度及JSON对象形式发布，以供后续研究使用。
数据集完整版本可通过以下链接获取：https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/A7NVF7

### 语言
英语

## 数据集结构
### 数据样例

{
"推文文本": "@RT_com: URGENT: Death toll in #Ecuador #quake rises to 233 – President #Correa #1 in #Pakistan",
"类别标签": "人员伤亡"
}

### 数据字段
* 推文文本：对应推文的正文内容
* 类别标签：对应为给定推文文本分配的分类标签

### 数据划分
* 训练集
* 开发集
* 测试集

## 数据集构建
推文采集自多起灾害事件。

### 标注信息
本数据集采用Amazon Mechanical Turk（AMT）进行标注，详细标注流程与规范请参考相关论文。
#### 标注人员来源
- 众包标注人员

### 授权信息
- CC BY-NC 4.0（知识共享署名-非商业性使用4.0国际许可协议）

### 引用信息

@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},
}