Add WORLDREP dataset

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README.md

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+---
+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
+---
+
+
+# WORLDREP: A Dataset for Analyzing and Predicting Global Relations
+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 features labeled relationships between countries with confidence 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                |
+| `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)
+

worldrep_dataset.csv

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