Add/update dataset card

README.md

@@ -1,29 +1,80 @@
 ---
-dataset_info:
-  features:
-  - name: symbol
-    dtype: string
-  - name: company_id
-    dtype: int64
-  - name: year
-    dtype: int64
-  - name: quarter
-    dtype: int64
-  - name: date
-    dtype: string
-  - name: tone_dispersion
-    dtype: float64
-  - name: call_key
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 3544142
-    num_examples: 33362
-  download_size: 2055546
-  dataset_size: 3544142
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+license: cc-by-4.0
+language:
+- en
+pretty_name: SP500 Tone Dataset
+tags:
+- financial
+- sentiment-analysis
+- regression
 ---
+
+# SP500 Tone Dataset
+
+## Dataset summary
+
+The SP500 Tone Dataset contains tone dispersion metrics extracted from earnings calls of S&P 500 companies. Each record represents a quarterly earnings call, capturing the variability in tone and sentiment expressed during the call. This dataset is useful for financial sentiment analysis, market prediction models, and studies on executive communication strategies.
+
+## Supported tasks
+
+- Regression (predicting tone dispersion)
+
+## Languages
+
+- English
+
+## Dataset structure
+
+| Field           | Type    | Description                                      |
+|-----------------|---------|--------------------------------------------------|
+| symbol          | string  | Stock ticker symbol for the company              |
+| company_id      | int64   | Unique identifier for the company                |
+| year            | int64   | Year of the earnings call                        |
+| quarter         | int64   | Quarter of the earnings call (1-4)               |
+| date            | string  | Date of the earnings call                        |
+| tone_dispersion | float64 | Measure of variability in tone during the call   |
+| call_key        | string  | Unique identifier for the specific earnings call |
+
+## Splits
+
+This dataset has a single split:
+- train: All records of tone dispersion metrics
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("kurrytran/sp500_tone_dataset")
+
+data = dataset["train"]
+
+# Example: Compute average tone dispersion by year
+from collections import defaultdict
+avg_tone_by_year = defaultdict(lambda: {"total": 0, "count": 0})
+for item in data:
+    year = item["year"]
+    avg_tone_by_year[year]["total"] += item["tone_dispersion"]
+    avg_tone_by_year[year]["count"] += 1
+
+for year, values in sorted(avg_tone_by_year.items()):
+    print(f"Year {year}: Average tone dispersion = {values['total'] / values['count']:.4f}")
+```
+
+## Citation
+
+If you use this dataset in your research, please cite it as follows:
+
+```bibtex
+@dataset{sp500_tone_dataset,
+  author    = {kurrytran},
+  title     = {SP500 Tone Dataset},
+  year      = {2025},
+  publisher = {Hugging Face},
+  url       = {https://huggingface.co/datasets/kurrytran/sp500_tone_dataset}
+}
+```
+
+## License
+
+This dataset is licensed under CC BY 4.0. For more details, see https://creativecommons.org/licenses/by/4.0/.