The dataset viewer is not available because its heuristics could not detect any supported data files. You can try uploading some data files, or configuring the data files location manually.
HalkTV-News Dataset
Dataset Summary
HalkTV-News is a Turkish news dataset containing 173,179 articles collected from Halk TV's news portal. Each article includes a title, summary, full content, and a source URL. The dataset is designed for tasks such as text classification, summarization, and topic modeling in Turkish. It provides a rich resource for understanding and modeling Turkish news content.
Supported Tasks and Leaderboards
- Text Summarization: With included summaries, the dataset can be used for abstractive or extractive summarization tasks.
- Text Classification: The dataset can be used to classify news articles into categories or topics.
- Sentiment Analysis: The content can be analyzed for sentiments in Turkish.
- Topic Modeling: Suitable for discovering hidden themes in news content.
Languages
The dataset is entirely in Turkish (tr).
Dataset Structure
The dataset contains the following columns:
Başlık: The title of the article.Özet: A brief summary of the article.İçerik: The full content of the article.Link: The URL linking to the full article on the Halk TV website.
Example Row:
| Başlık | Özet | İçerik | Link |
|---|---|---|---|
| Kepçe operatörüne yol gösterirken... | Artvin’in Şavşat ilçesinde... | İlçeye bağlı Maden... | https://halktv.com.tr/gundem/kepce-operator... |
Data Splits
The dataset is provided as a single split with 173,180 examples. Users can split the dataset into train, validation, and test sets as needed.
Source Data
The dataset was collected from Halk TV's publicly available news portal. The articles were programmatically scraped and processed to extract relevant metadata such as title, summary, and content.
Licensing Information
This dataset is available for research purposes only. Please ensure compliance with the original data sources' terms of use.
Citation
If you use this dataset, please cite the following:
- N. Z. Kayalı and S. I. Omurca, "HTV-News: A New Dataset with High Novelty Rate for Turkish Text Summarization," 2024 9th International Conference on Computer Science and Engineering (UBMK), Antalya, Turkiye, 2024, pp. 1-6, doi: 10.1109/UBMK63289.2024.10773431. https://ieeexplore.ieee.org/document/10773431
- Downloads last month
- 2