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---
dataset_info:
  features:
  - name: url
    dtype: string
  - name: title
    dtype: string
  - name: base_url
    dtype: string
  - name: text
    dtype: string
  - name: Court
    dtype: int64
  - name: Covid
    dtype: int64
  - name: Culture
    dtype: int64
  - name: EU
    dtype: int64
  - name: Economy
    dtype: int64
  - name: Education
    dtype: int64
  - name: Entertainment
    dtype: int64
  - name: Environment
    dtype: int64
  - name: Health
    dtype: int64
  - name: Immigration
    dtype: int64
  - name: International
    dtype: int64
  - name: Opinion
    dtype: int64
  - name: Politics
    dtype: int64
  - name: Religion
    dtype: int64
  - name: Social
    dtype: int64
  - name: Sports
    dtype: int64
  - name: Transport
    dtype: int64
  splits:
  - name: train
    num_bytes: 21018894
    num_examples: 10784
  - name: validation
    num_bytes: 4566883
    num_examples: 2293
  - name: test
    num_bytes: 4840844
    num_examples: 2297
  download_size: 16607591
  dataset_size: 30426621
license: cc-by-nc-sa-4.0
task_categories:
- text-classification
language:
- mt
pretty_name: Maltese News Categories
size_categories:
- 10K<n<100K
---
# Maltese News Categories

A multi-label topic classification dataset for Maltese News Articles.

## Data Collection

The data was collected from the [`press_mt` subset from Korpus Malti v4.0](https://huggingface.co/datasets/MLRS/korpus_malti/viewer/press_mt).
Article contents were cleaned to filter out JavaScript, CSS, & repeated non-Maltese sub-headings.
The labels are based on the `category` field from this corpus.
Additional filtering & cleaning was performed as follows:
1. Documents with generic categories (`News`, `Local`, `Headlines`, `Uncategorised`, `Archived`) were ignored.
2. Some categories were merged as deemed necessary by native Maltese speakers to standardise tags assigned by different news portals (for example merging `European Union` & `Unjoni Ewropea` under `EU`).
3. Articles with categories having less than 100 articles were ignored.
4. Categories having a >75% co-occurence with another category are dropped.

The different tags & their distribution is shown in the following table.

| Tag           | Token Count  | Article Count | Article Percentage |
| ------------- | ------------ | ------------- | ------------------ |
| Court         |      404,329 |           860 |               5.59 |
| Covid         |      458,120 |         1,735 |              11.29 |
| Culture       |      750,406 |         2,186 |              14.22 |
| EU            |       93,227 |           240 |               1.56 |
| Economy       |      112,972 |           321 |               2.09 |
| Education     |       56,084 |           191 |               1.24 |
| Entertainment |      837,248 |         3,147 |              20.47 |
| Environment   |       38,522 |           147 |               0.96 |
| Health        |       81,630 |           290 |               1.89 |
| Immigration   |       29,665 |           120 |               0.78 |
| International |      784,878 |         3,957 |              25.74 |
| Opinion       |      231,266 |           321 |               2.09 |
| Politics      |      682,007 |         1,294 |               8.42 |
| Religion      |      186,300 |           465 |               3.02 |
| Social        |       98,127 |           203 |               1.32 |
| Sports        |      835,484 |         3,066 |              19.94 |
| Transport     |       74,959 |           241 |               1.57 |

## Additional Information

### License

This work is licensed under a [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License][cc-by-nc-sa].
Permissions beyond the scope of this license may be available at [https://mlrs.research.um.edu.mt/](https://mlrs.research.um.edu.mt/).

[![CC BY-NC-SA 4.0][cc-by-nc-sa-image]][cc-by-nc-sa]

[cc-by-nc-sa]: http://creativecommons.org/licenses/by-nc-sa/4.0/
[cc-by-nc-sa-image]: https://licensebuttons.net/l/by-nc-sa/4.0/88x31.png

## Citation

This work was first presented in [Topic Classification and Headline Generation for Maltese using a Public News Corpus](#).
Cite it as follows: 

```bibtex
@inproceedings{maltese-news-datasets,
    title = "Topic Classification and Headline Generation for {M}altese using a Public News Corpus",
    author = "Chaudhary, Amit Kumar  and
              Micallef, Kurt  and
              Borg, Claudia",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation",
    month = may,
    year = "2024",
    publisher = "Association for Computational Linguistics",
}
```