---
license: apache-2.0
language:
- de
- id
- 'no'
- hu
- tl
- cs
- da
- vi
- nl
- lv
- tr
- sl
- af
- sw
- fi
- cy
- sq
- hr
- lt
- et
- en
- fr
- sv
- it
- so
- es
- bn
- pl
- ca
- sk
- pt
- ro
task_categories:
- text-classification
- zero-shot-classification
tags:
- nlp
size_categories:
- 10K<n<100K
---
**I have decided to release the auto-moderation models all at once sometime in July, 2023. The curated datasets for training these models will be avaliable first.**

<br>


This is a large corpus of 41,578 preprocessed sms spam messages and emails sent by humans in 32 languages.

<br>

### Some preprcoessing algorithms
- [spam_assassin.js](./spam_assassin.js), followed by [spam_assassin.py](./spam_assassin.py)
- [enron_spam.py](./enron_spam.py)

<br>

### Data composition
![Spam vs Non-spam (Ham)](https://i.imgur.com/9hBvc37.png)

<br>

### Description
To make the text format between sms messages and emails consistent, email subjects and content are separated by two newlines:

```python
text = email.subject + "\n\n" + email.content
```

<br>

### Original source
- https://huggingface.co/datasets/sms_spam
- https://github.com/MWiechmann/enron_spam_data
- https://github.com/stdlib-js/datasets-spam-assassin
- https://repository.ortolang.fr/api/content/comere/v3.3/cmr-simuligne.html