# Keyterm Sentiment Analytics Metrics

## Example code

```python
from finter.data import ContentFactory
cf = ContentFactory("kr_stock", 20240101, 20240201)

# sentiment_us category
df = cf.get_df("all-N_of_mat_key[all_cat]", cagegory='sentiment')

# sentiment_exp_us category
df = cf.get_df("all-N_of_mat_key[all_cat]", cagegory='sentiment_exp')
```

## Metadata

| Valid From | Delivery Schedule  | Time Zone  | Data Frequency |
| ---------- | ------------------ | ---------- | -------------- |
| 2005-01-01 | UTC 00 21 \* \* \* | Asia/Seoul | 1d             |

## Item List

* Use `sentiment` category for Korea
* Use `sentiment_exp` category for Korea Expanded

### All Sentiment

* `all-N_of_mat_key[all_cat]`: Number of total key terms for overall sentiment on the given day in Korea.
* `all-N_of_mat_key[in_cat]`: Number of matching key terms for overall sentiment in the specified category on the given day in Korea.
* `all-N_of_news`: Number of total news articles for overall sentiment on the given day in Korea.
* `all-mat_key_rate[in_cat%all_cat]`: Category key term rate for overall sentiment on the given day in Korea.

### Negative Sentiment

* `neg-N_of_mat_key[all_cat]`: Number of total key terms for negative sentiment on the given day in Korea.
* `neg-N_of_mat_key[in_cat]`: Number of matching key terms for negative sentiment in the specified category on the given day in Korea.
* `neg-N_of_news`: Number of total news articles for negative sentiment on the given day in Korea.
* `neg-mat_key_rate[in_cat%all_cat]`: Category key term rate for negative sentiment on the given day in Korea.

### Neutral Sentiment

* `neu-N_of_mat_key[all_cat]`: Number of total key terms for neutral sentiment on the given day in Korea.
* `neu-N_of_mat_key[in_cat]`: Number of matching key terms for neutral sentiment in the specified category on the given day in Korea.
* `neu-N_of_news`: Number of total news articles for neutral sentiment on the given day in Korea.
* `neu-mat_key_rate[in_cat%all_cat]`: Category key term rate for neutral sentiment on the given day in Korea.

### Positive Sentiment

* `pos-N_of_mat_key[all_cat]`: Number of total key terms for positive sentiment on the given day in Korea.
* `pos-N_of_mat_key[in_cat]`: Number of matching key terms for positive sentiment in the specified category on the given day in Korea.
* `pos-N_of_news`: Number of total news articles for positive sentiment on the given day in Korea.
* `pos-mat_key_rate[in_cat%all_cat]`: Category key term rate for positive sentiment on the given day in Korea.


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