metadata

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. 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:

Documents with generic categories (News, Local, Headlines, Uncategorised, Archived) were ignored.
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).
Articles with categories having less than 100 articles were ignored.
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. Permissions beyond the scope of this license may be available at https://mlrs.research.um.edu.mt/.

Citation

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

@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",
}