| --- |
| license: cc-by-nc-4.0 |
| task_categories: |
| - text-classification |
| language: |
| - en |
| tags: |
| - event-forecasting |
| - international-relations |
| - geopolitics |
| - text-classification |
| pretty_name: WORLDREP |
| size_categories: |
| - 100K<n<1M |
| dataset_info: |
| features: |
| - name: EventID |
| dtype: string |
| - name: SourceURL |
| dtype: string |
| - name: DATE |
| dtype: string |
| - name: CONTENT |
| dtype: string |
| - name: Country1 |
| dtype: string |
| - name: Country2 |
| dtype: string |
| - name: Score |
| dtype: float64 |
| splits: |
| - name: train |
| num_bytes: 19348381 |
| num_examples: 147697 |
| download_size: 2949164 |
| dataset_size: 19348381 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| --- |
| |
|
|
| # WORLDREP: A Dataset for Forecasting Future International Events |
| WORLDREP (**WORLD Relationship and Event Prediction**) is a high-quality dataset designed for predicting future international events based on textual information, such as news articles. It provides the relationships between countries with numerical scores ranging from **0.0 (cooperation)** to **1.0 (conflict)**. |
|
|
| ## Dataset Overview |
|
|
| This dataset was introduced in: |
| **Forecasting Future International Events: A Reliable Dataset for Text-Based Event Modeling** ([Link](https://arxiv.org/abs/2411.14042)) |
|
|
| ### **Dataset Structure** |
| | Column | Description | |
| |--------------|-----------------------------------------------------------------------------| |
| | `EventID` | Unique identifier for the event | |
| | `SourceURL` | URL of the news article reporting the event | |
| | `DATE` | Publication date of the article in `YYYYMMDDHHMMSS` format | |
| | `CONTENT` | Content of the news article | |
| | `Country1` | The first country involved in the event | |
| | `Country2` | The second country involved in the event | |
| | `Score` | Numerical value (0.0-1.0) representing the relationship between countries. A score close to **0.0** indicates **cooperation**, while a score close to **1.0** indicates **conflict**. | |
|
|
| ## Applications |
| - Predicting future international events |
| - Understanding geopolitical trends |
| - Training machine learning models for event forecasting |
|
|
| ## License |
| This dataset is licensed under the [Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). |
|
|
| ## Citation |
| If you use this dataset, please cite the corresponding paper: |
|
|
| ``` |
| @inproceedings{gwak2024worldrep, |
| title={Forecasting Future International Events: A Reliable Dataset for Text-Based Event Modeling}, |
| author={Daehoon Gwak, Junwoo Park, Minho Park, Chaehun Park, Hyunchan Lee, Edward Choi and Jaegul Choo}, |
| booktitle={EMNLP Findings}, |
| year={2024} |
| } |
| ``` |
|
|
| ### Related Resources |
| - [Paper](https://arxiv.org/abs/2411.14042) |
| - [GitHub Repository for WORLDREP](https://github.com/eogns282/WORLDREP) |
