Datasets:
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---
license: mit
task_categories:
- text-classification
language:
- en
size_categories:
- 1K<n<10K
tags:
- binary-classification
- tweets
- natural-language-processing
pretty_name: Disaster vs Non-Disaster Tweets
configs:
- config_name: default
data_files:
- split: train
path: "train.csv"
- split: test
path: "test.csv"
---
# Disaster Tweets Dataset For Binary Classification
This dataset contains tweets classified as either disastrous (`label 1`) or not disastrous (`label 0`). It is designed to train and evaluate machine learning models for disaster-related tweet classification.
## Files Included
- `train.csv`: Contains **7,613** tweets with their respective labels.
- `test.csv`: Contains **3,263** tweets without labels.
## Columns
Each CSV file contains the following columns:
- `id` – Unique identifier for each tweet.
- `keyword` – A keyword extracted from the tweet (may be blank).
- `location` – The geographical location where the tweet was posted (may be blank).
- `text` – The actual content of the tweet.
- (`label` in `train.csv`) – Classification of the tweet:
- `1` → Disastrous
- `0` → Not Disastrous
## Example Rows
### `train.csv` (Sample Data)
| id | keyword | location | text | label |
|-----|---------|--------------|------------------------------------------------------------------------------------------|-------|
| 1 | | | Just happened a terrible car crash | 1 |
| 2 | | | Heard about #earthquake in different cities, stay safe everyone! | 1 |
| 3 | | | Forest fire spotted at the park. Geese are fleeing across the street! | 1 |
| 10 | | | No I don’t like cold weather! | 0 |
| 52 | ablaze | Philadelphia | Crying out for more! Set me ablaze | 0 |
### `test.csv` (Sample Data)
| id | keyword | location | text |
|-----|---------|----------|-----------------------------------------------------------------------------------------|
| 11 | | | Typhoon Soudelor kills 28 in China and Taiwan |
| 46 | ablaze | London | Birmingham Wholesale Market is ablaze! Fire breaks out at Birmingham's Wholesale Market |
| 51 | ablaze | NIGERIA | Toke Makinwa’s marriage crisis sets Nigerian Twitter ablaze… |
## Contributing
If you would like to improve or expand the dataset, feel free to submit suggestions or contributions. Feedback is always welcome! |