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 as part of our research article: Mastrokostas, C., Giarelis, N., & Karacapilidis, N. (2024). Social Media Topic Classification on Greek Reddit For information about dataset creation, limitations etc. see the original article.

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

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}
}