| | --- |
| | license: apache-2.0 |
| | language: |
| | - el |
| | pipeline_tag: text-classification |
| | task_categories: |
| | - text-classification |
| | - text-generation |
| | - zero-shot-classification |
| | task_ids: |
| | - multi-class-classification |
| | - topic-classification |
| | tags: |
| | - Social Media |
| | - Reddit |
| | - Greek NLP |
| | - Text Classification |
| | - Topic Classification |
| | - Title Generation |
| | pretty_name: Greek Reddit |
| | size_categories: |
| | - 1K<n<10K |
| | --- |
| | |
| | # GreekReddit |
| |
|
| | A Greek topic classification dataset collected from Greek subreddits, which contains 6,534 posts, their titles and topic labels. |
| | This dataset has been used to train our best-performing model [Greek-Reddit-BERT](https://huggingface.co/IMISLab/Greek-Reddit-BERT) as part of our research article: |
| | [Mastrokostas, C., Giarelis, N., & Karacapilidis, N. (2024). Social Media Topic Classification on Greek Reddit](https://www.mdpi.com/2078-2489/15/9/521) |
| | For information about dataset creation, limitations etc. see the original article. |
| |
|
| | <img src="Greek Reddit icon.svg" width="200"/> |
| |
|
| | ### Supported Tasks and Leaderboards |
| |
|
| | This dataset supports: |
| |
|
| | **Multi-class Text Classification:** Given the text of a post, a model learns to predict the associated topic label. |
| | **Title Generation:** Given the text of a post, a text generation model learns to generate a post title. |
| |
|
| | ### Languages |
| |
|
| | All posts are written in Greek. |
| |
|
| | ## Dataset Structure |
| |
|
| | ### Data Instances |
| |
|
| | The dataset is structured as a `.csv` file, while three dataset splits are provided (train, validation and test). |
| |
|
| | ### Data Fields |
| |
|
| | The following data fields are provided for each split: |
| |
|
| | `id`: (**str**) A unique post id. |
| | `title`: (**str**) A short post title. |
| | `text`: (**str**) The full text of the post. |
| | `url`: (**str**) The URL which links to the original unprocessed post. |
| | `category`: (**str**): The class label of the post. |
| |
|
| | ### Data Splits |
| |
|
| | |Split|No of Documents| |
| | |-------------------|------------------------------------| |
| | |Train|5,530| |
| | |Validation|504| |
| | |Test|500| |
| |
|
| | ### Example code |
| | ```python |
| | from datasets import load_dataset |
| | |
| | # Load the training, validation and test dataset splits. |
| | train_split = load_dataset('IMISLab/GreekReddit', split = 'train') |
| | validation_split = load_dataset('IMISLab/GreekReddit', split = 'validation') |
| | test_split = load_dataset('IMISLab/GreekReddit', split = 'test') |
| | |
| | print(test_split[0]) |
| | ``` |
| | ## Contact |
| |
|
| | If you have any questions/feedback about the dataset please e-mail one of the following authors: |
| | ``` |
| | giarelis@ceid.upatras.gr |
| | cmastrokostas@ac.upatras.gr |
| | karacap@upatras.gr |
| | ``` |
| | ## Citation |
| |
|
| | ``` |
| | @article{mastrokostas2024social, |
| | title={Social Media Topic Classification on Greek Reddit}, |
| | author={Mastrokostas, Charalampos and Giarelis, Nikolaos and Karacapilidis, Nikos}, |
| | journal={Information}, |
| | volume={15}, |
| | number={9}, |
| | pages={521}, |
| | year={2024}, |
| | publisher={Multidisciplinary Digital Publishing Institute} |
| | } |
| | ``` |
