---
license: apache-2.0
language:
- en
tags:
- clickbait
- not
- binary_classification
task_categories:
- text-classification
---

- 37.870 texts in  total, 17.850 NOT clickbait texts and 20.020 CLICKBAIT texts
- All duplicate values were removed
- Split using sklearn into 80% train and 20% temporary test (stratified label). Then split the test set using 0.50% test and validation (stratified label)
- Split: 80/10/10
- Train set label distribution: 0 ==> 14.280, 1 ==> 16.016
- Validation set label distribution: 0 ==> 1.785, 1 ==> 2.002
- Test set label distribution: 0 ==> 1.785, 1 ==> 2.002

- The dataset was created from the combination of other available datasets online. Their links are available here:
- https://www.kaggle.com/datasets/amananandrai/clickbait-dataset
- https://www.kaggle.com/datasets/thelazyaz/youtube-clickbait-classification?resource=download
- https://www.kaggle.com/datasets/vikassingh1996/news-clickbait-dataset?select=train2.csv
- https://www.kaggle.com/competitions/clickbait-news-detection/data?select=train.csv
- https://www.kaggle.com/competitions/clickbait-news-detection/data?select=valid.csv
- https://zenodo.org/records/6362726#.YsbdSTVBzrk