Datasets:

vichetkao
/

Scam_Message_9_Language

license: mit
task_categories:
  - text-classification
language:
  - en
  - zh
  - de
  - fr
  - hi
  - km
  - ru
  - th
  - vi
tags:
  - spam-detection
  - scam-detection
  - phishing-detection
  - multilingual
  - sms
  - text-classification
pretty_name: Multilingual Scam Spam/Ham Dataset
size_categories:
  - 10K<n<100K
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-00000-of-00001.parquet

Multilingual Scam Spam/Ham Dataset

This dataset contains multilingual text samples labeled for binary spam/scam detection. Each example is either ham or spam.

Dataset Details

Task: binary text classification
Rows: 12,800
Format: Parquet
Split: train
Labels:
- 0: ham
- 1: spam
Languages: English, Chinese, German, French, Hindi, Khmer, Russian, Thai, Vietnamese

Columns

Column	Type	Description
`text`	string	Message text
`label`	int64	Classification label, where `0` is ham and `1` is spam
`language`	string	Language code from the source folder

Load With Hugging Face Datasets

from datasets import load_dataset

dataset = load_dataset("parquet", data_files="data/train-00000-of-00001.parquet")

print(dataset)
print(dataset["train"][0])

After uploading this folder to the Hugging Face Hub, you can load it with:

from datasets import load_dataset

dataset = load_dataset("your-username/your-dataset-name")

Intended Use

This dataset can be used to train and evaluate models for:

spam message detection
scam text detection
phishing-style message classification
multilingual safety filtering experiments

Label Meaning

0 = ham
1 = spam

Dataset Structure

hf_dataset_parquet/
├── README.md
└── data/
    └── train-00000-of-00001.parquet

Notes

The dataset was converted from cleaned CSV files in dataset_clean, where each language folder contains separate spam.csv and ham.csv files.