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