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README.md

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+---
+task_categories:
+- text-classification
+language:
+- en
+tags:
+- headlines
+- click-through-rate
+- preference-learning
+- engagement-prediction
+size_categories:
+- 10K<n<100K
+---
+
+# Headlines CTR Dataset
+
+This dataset contains pairs of news headlines with labels indicating which headline received more clicks. It's designed for studying what makes headlines engaging and for training models to predict user preferences.
+
+## Dataset Description
+
+Each example contains two competing headlines (A and B) that were shown to users, along with engagement metrics and a binary label indicating which performed better.
+
+### Dataset Statistics
+- **Train**: 8,781 headline pairs
+- **Validation**: 1,019 headline pairs  
+- **Holdout**: 4,357 headline pairs
+- **Total**: 14,157 headline pairs
+
+### Features
+
+Each example contains:
+- `headline_A`: First headline text
+- `headline_B`: Second headline text
+- `label_pairwise`: 1 if headline A got more clicks, 0 if B got more
+- `ctr_A`: Click-through rate for headline A
+- `ctr_B`: Click-through rate for headline B
+- `ctr_diff`: Difference in CTR (A - B)
+- `counts_A`: [clicks, impressions] for headline A
+- `counts_B`: [clicks, impressions] for headline B
+- `test_id`: Unique identifier for the A/B test
+- `eyecatcher_id`: Identifier for the content piece
+- `created_at`: Timestamp of the test
+- `headlines_concat`: Pre-concatenated text for convenience
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+# Load the dataset
+dataset = load_dataset("Yanjo/headlines-ctr")
+
+# Access different splits
+train_data = dataset["train"]
+val_data = dataset["validation"]
+holdout_data = dataset["holdout"]
+
+# Example: Get the first training example
+example = train_data[0]
+print(f"Headline A: {example['headline_A']}")
+print(f"Headline B: {example['headline_B']}")
+print(f"Winner: {'A' if example['label_pairwise'] == 1 else 'B'}")
+```
+
+## Example
+
+```python
+{
+    'headline_A': 'Nearly 75% of our crops have vanished in the last 100 years...',
+    'headline_B': '100 years ago, people were eating things that most of us will never taste.',
+    'label_pairwise': 0,  # B performed better
+    'ctr_A': 0.0013,
+    'ctr_B': 0.0058,
+    'ctr_diff': -0.0044
+}
+```
+
+## Applications
+
+This dataset can be used for:
+- Training models to predict headline engagement
+- Studying linguistic features that drive clicks
+- A/B testing analysis
+- Preference learning research
+- Natural language understanding of persuasive text
+
+## Citation
+
+If you use this dataset, please cite:
+```bibtex
+@misc{headlines-ctr,
+  title={Headlines CTR Dataset},
+  author={Yanjo},
+  year={2024},
+  publisher={HuggingFace}
+}
+```
+
+## License
+
+Please check with the original data source for licensing information.