README.md

---
language:
  - bn
license: cc-by-4.0
task_categories:
  - text-classification
task_ids:
  - multi-class-classification
pretty_name: Bangla Emergency Posts
size_categories:
  - 1K<n<10K
tags:
  - bangla
  - bengali
  - emergency
  - social-media
  - crisis-informatics
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train.csv
      - split: validation
        path: data/validation.csv
      - split: test
        path: data/test.csv
  - config_name: full
    data_files:
      - split: full
        path: data/bangla_emergency_posts.csv
---

# Bangla Emergency Posts

5,836 Bangla social media posts, hand-labelled into nine emergency categories.
Built for *Bangla Emergency Post Classification on Social Media using Transformer
Based BERT Models* (EICT 2023).

Emergency text classification in Bangla is scarce despite the language having
hundreds of millions of speakers. This dataset exists so that Bangla-speaking
people can report emergencies in their own language and have those reports
routed automatically.

## Usage

```python
from datasets import load_dataset

ds = load_dataset("NightRaven/bangla-emergency-posts")
print(ds["train"][0])
# {'content': 'ভূমিকম্পের পর স্কুলবাড়ি ভেঙে পড়ে। ...', 'label': 'natural_disaster'}
```

## Fields

| field | type | description |
|---|---|---|
| `content` | string | the post text, Bangla with occasional English words |
| `label` | string | one of the nine categories below |

Labels are stored as strings. Where an integer id is needed, the models trained
on this data use alphabetical order:

| id | label | id | label | id | label |
|----|-------|----|-------|----|-------|
| 0 | accident | 3 | fire | 6 | suicide |
| 1 | blood | 4 | natural_disaster | 7 | war |
| 2 | crime | 5 | pandemic | 8 | weather |

`blood` covers urgent blood-donation appeals, a common and distinct category of
emergency post in Bangla social media.

## Splits

Stratified 56 / 14 / 30.

| label | train | validation | test | total |
|---|---:|---:|---:|---:|
| accident | 579 | 123 | 301 | 1,003 |
| blood | 123 | 31 | 66 | 220 |
| crime | 1,355 | 372 | 765 | 2,492 |
| fire | 295 | 82 | 122 | 499 |
| natural_disaster | 277 | 64 | 153 | 494 |
| pandemic | 83 | 24 | 40 | 147 |
| suicide | 114 | 33 | 61 | 208 |
| war | 104 | 20 | 51 | 175 |
| weather | 337 | 70 | 191 | 598 |
| **total** | **3,267** | **819** | **1,750** | **5,836** |

## Collection and labelling

Posts were gathered from Facebook, Twitter and Bangladeshi daily newspapers,
covering events in Bangladesh and neighbouring India. Labelling was done by hand
by native Bangla speakers.

Collecting structured Bangla social media text is difficult — stemming rules are
hard to pin down and stopword lists are inconsistent — so the data was labelled
manually rather than filtered heuristically.





## Citation

```bibtex
@inproceedings{nabil2023bangla,
  title     = {Bangla Emergency Post Classification on Social Media using
               Transformer Based BERT Models},
  author    = {Nabil, Alvi Ahmmed and Arifeen, Shamsul and Das, Dola and
               Salim, Md. Shahidul and Fattah, H. M. Abdul},
  booktitle = {6th International Conference on Electrical Information and
               Communication Technology (EICT)},
  address   = {Khulna, Bangladesh},
  year      = {2023}
}
```

Models trained on this dataset:
[NightRaven/bangla-emergency-post-classification](https://huggingface.co/NightRaven/bangla-emergency-post-classification)