Datasets:
Dataset Card for Tajik News Binary Classification
Dataset Details
Dataset Description
This dataset contains 16,812 Tajik news articles labeled for binary classification between news (label=1) and analytics (label=0). The data are perfectly balanced: 8,406 news articles and 8,406 analytical pieces. It is intended as a benchmark for distinguishing factual news from opinion/analytical content in the Tajik language. The articles have been cleaned, deduplicated, and filtered to ensure quality.
- Curated by: Arabov Mullosharaf Kurbonovich
- Language(s) (NLP): Tajik (
tg) - License:
other– see Licensing & Legal Notice below.
Licensing & Legal Notice
This dataset follows the practice established by large web‑crawled corpora such as HPLT and OSCAR:
- Original source texts (news articles) remain the property of their respective authors and publishers. They are not owned by the dataset curator and are not covered by the CC BY‑SA 4.0 license.
- The structured compilation, metadata, and any original annotations created during dataset preparation are released under the CC BY‑SA 4.0 license.
- Users are solely responsible for ensuring their use of the underlying texts complies with applicable copyright law. For commercial use of verbatim excerpts, permission from the original copyright holders may be required.
- A notice‑and‑takedown procedure is in place: rights holders can request removal of specific content by contacting the dataset maintainers (see Dataset Card Contact). We commit to responding within 14 business days and removing disputed content in the next release.
Dataset Sources
Uses
Direct Use
The dataset can be used for:
- Training and evaluating binary classifiers (news vs. analytics)
- Benchmarking Tajik language models on a simple classification task
- Educational purposes in NLP for low-resource languages
Out-of-Scope Use
The dataset is not intended for multiclass or multilabel classification; separate datasets are available for those tasks.
Dataset Structure
Data Fields
| Field | Type | Description |
|---|---|---|
content |
string | Full text of the article (title + body, concatenated with \n\n) |
title |
string | Article headline |
label |
int64 | 1 for news, 0 for analytics |
label_text |
string | Textual description of the label ("news" or "analytics") |
category |
string | Original normalized category from the source (e.g., Хабарҳо / News, Ҷамъият / Society) |
content_length |
int64 | Length of content in characters |
resource |
string | URL of the article (if available) |
date |
string | Publication date (if available; otherwise empty) |
Data Splits
The dataset contains a single split (train) with all 16,812 records. For evaluation, users should create their own train/validation/test splits (e.g., 80/10/10).
Class Distribution
| Class | Label | Count | Percentage |
|---|---|---|---|
| News | 1 | 8,406 | 50.0% |
| Analytics | 0 | 8,406 | 50.0% |
Top Categories (Original)
| Category (Tajik) | Category (English) | Count | Percentage |
|---|---|---|---|
| Хабарҳо | News | 8,406 | 50.0% |
| Ҷамъият | Society | 2,170 | 12.9% |
| Иқтисод | Economy | 1,151 | 6.8% |
| Сиёсат | Politics | 1,035 | 6.2% |
| Ҳодиса | Incidents | 812 | 4.8% |
| Амният | Security | 769 | 4.6% |
| Тоҷикистон | Tajikistan | 460 | 2.7% |
| Фарҳанг | Culture | 453 | 2.7% |
| Варзиш | Sports | 333 | 2.0% |
| Ҳукумат | Government | 241 | 1.4% |
Dataset Creation
Curation Rationale
The dataset was created to provide a balanced binary classification task for Tajik, separating hard news from analytical/opinion pieces. This is a common real‑world application where automatic detection of news vs. commentary is valuable.
Source Data
Data Collection and Processing
- Collection: Articles were collected from eight Tajik news portals between 2015 and 2025.
- Cleaning: HTML removed, whitespace normalized, deduplicated, filtered by length (50–10,000 characters).
- Labeling: News articles were defined as those with the normalized category Хабарҳо (News). Analytics were all other articles (e.g., Society, Economy, Politics, Culture). The dataset was balanced by undersampling the majority class to match the number of news articles.
- Final Format: Each article is stored with the binary label and the original category.
Who are the source data producers?
The original content was produced by the news portals listed in the cluster dataset card.
Annotations
Labels are derived from the normalized categories. News = Хабарҳо (News); all other categories = analytics. This is a simple, rule‑based labeling suitable for the intended binary task.
Personal and Sensitive Information
The dataset contains publicly available news articles; no additional personal information is included.
Bias, Risks, and Limitations
- Label definition: The distinction between "news" and "analytics" is based solely on the source category. Some articles labeled as analytics may still contain factual news, and some news articles may contain opinion elements.
- Source imbalance: The majority of articles come from
asiaplus.tj(62% of the original corpus), though undersampling may have reduced this effect. - Date coverage: Not all articles have reliable dates.
Recommendations
- Evaluate on a held‑out set that reflects the original distribution of sources.
- Consider that the binary labels may have some noise; cross‑validation is recommended.
Citation
BibTeX (dataset):
@misc{arabov2026tajikbinary,
author = {Arabov, Mullosharaf Kurbonovich},
title = {Tajik News Binary Classification Dataset},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/TajikNLPWorld/tajik-news-binary}
}
APA (dataset): Arabov, M. K. (2026). Tajik News Binary Classification Dataset [Data set]. Hugging Face. https://huggingface.co/datasets/TajikNLPWorld/tajik-news-binary
Glossary
- Binary classification – a task where each input is assigned one of two possible categories.
- Low-resource language – a language with limited digital resources and tools.
More Information
For questions, contributions, or feedback, please open an issue on the Hugging Face repository.
Dataset Card Authors
- Arabov Mullosharaf Kurbonovich (TajikNLPWorld)
Dataset Card Contact
For questions, takedown requests, or collaboration, please open an issue on the Hugging Face repository:
https://huggingface.co/datasets/TajikNLPWorld/tajik-news-binary/discussions
📧 Direct email: cool.araby@gmail.com
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