Financial News Scraper + Sentiment Analysis Application

An interactive application that takes either text or article URL as input and outputs sentiment of every sentence in the article. The sentiment is obtained using a fine-tuned BERT model on financial news articles. The performance of the model is compared (side-by-side) in the table with other out-of-thebox models (in this case textblob).

TEST OUT THE APP <==

URL used in demo

Table Column Descriptions

1. Sentence: Input sentence
2. prediction: Predicted sentiment for sentence using custom model.
3. sentiment_score: Sentiment Score using custom/fine-tuned BERT model.
4. textblob_prediction: Sentiment using out of the box textblob sentiment analyzer.