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)

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).

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
• GitHub Repository for WORLDREP