# Medical Dataset Classification for Kurdish Short Text over Social Media

arXiv: https://arxiv.org/abs/2204.09660 · HTML: https://mlsanity.com/paper/2204.09660/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 10 references that are in the map.
- First posted on arXiv 26 Mar 2022.

## Builds on (most cited first, 1 of 1)

- [Performance evaluation results of evolutionary clustering algorithm star for clustering heterogeneous datasets](https://mlsanity.com/paper/2105.02810/) (2021)

## Abstract (arXiv)

The Facebook application is used as a resource for collecting the comments of this dataset, The dataset consists of 6756 comments to create a Medical Kurdish Dataset (MKD). The samples are comments of users, which are gathered from different posts of pages (Medical, News, Economy, Education, and Sport). Six steps as a preprocessing technique are performed on the raw dataset to clean and remove noise in the comments by replacing characters. The comments (short text) are labeled for positive class (medical comment) and negative class (non-medical comment) as text classification. The percentage ratio of the negative class is 55% while the positive class is 45%.