Spam Classification
task903_deceptive_opinion_spam_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task903_deceptive_opinion_spam_classification
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task903_deceptive_opinion_spam_classification.task902_deceptive_opinion_spam_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task902_deceptive_opinion_spam_classification
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task902_deceptive_opinion_spam_classification.sms-spam-classificationemail-spam-classification
Email Spam Classification
The dataset consists of a collection of emails categorized into two major classes: spam and not spam. It is designed to facilitate the development and evaluation of spam detection or email filtering systems.
The spam emails in the dataset are typically unsolicited and unwanted messages that aim to promote products or services, spread malware, or deceive recipients for various malicious purposes. These emails often contain misleading subject lines… See the full description on the dataset page: https://huggingface.co/datasets/UniqueData/email-spam-classification.spam-reviews-vie-classification
SpamReviews_vie_Classification
Deduplicated copy of kornwtp/spam-reviews-vie-classification.
Splits
split
rows
test
3,972
train
14,242
validation
1,589
zhiznmart-spam-classification
ZhiznMart Spam Classification
Русскоязычный набор сообщений для бинарной классификации спама в Telegram. Данные сформированы на основе сообщений из одного из чатов филиала компании «Жизньмарт» и использовались при разработке систем модерации DespamLy Telegram Bot и LifeMart Safety.
Состав
Файл messages.csv содержит 5 648 строк и два поля:
Поле
Тип
Описание
message
string
Текст сообщения
label
int
0 — не спам, 1 — спам
Распределение классов: 2 953… See the full description on the dataset page: https://huggingface.co/datasets/necrasov-ilya/zhiznmart-spam-classification.