Keyterm Sentiment Analytics Metrics

This dataset provides metrics on news articles, segmented by sentiment (positive, negative, neutral) and category, including rates and counts of materials.

Example code

from finter.data import ContentFactory
cf = ContentFactory("us_stock", 20240101, 20240201)

# sentiment_us category
df = cf.get_df("all-mat_cat_rate", cagegory='sentiment_us')

# sentiment_exp_us category
df = cf.get_df("all-mat_cat_rate", cagegory='sentiment_exp_us')

Metadata

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

Item List

• Use sentiment_us category for US

• Use sentiment_exp_us category for US Expanded

All Sentiment

• all-mat_cat_rate: Category rate for overall sentiment on the given day in the U.S.

• all-N_of_mat_cat_each: Number of news articles for overall sentiment in each category on the given day in the U.S.

• all-N_of_news: Number of total news articles for overall sentiment on the given day in the U.S.

Negative Sentiment

• neg-mat_cat_rate: Category rate for negative sentiment on the given day in the U.S.

• neg-N_of_mat_cat_each: Number of news articles for negative sentiment in each category on the given day in the U.S.

• neg-N_of_news: Number of total news articles for negative sentiment on the given day in the U.S.

Neutral Sentiment

• neu-mat_cat_rate: Category rate for neutral sentiment on the given day in the U.S.

• neu-N_of_mat_cat_each: Number of news articles for neutral sentiment in each category on the given day in the U.S.

• neu-N_of_news: Number of total news articles for neutral sentiment on the given day in the U.S.

Positive Sentiment

• pos-mat_cat_rate: Category rate for positive sentiment on the given day in the U.S.

• pos-N_of_mat_cat_each: Number of news articles for positive sentiment in each category on the given day in the U.S.

• pos-N_of_news: Number of total news articles for positive sentiment on the given day in the U.S.