Finance News Sentiments

Finance news labeled by their sentiment. Can be used for NLP.

Here are the data operations made on the texts:

Nulls removal Duplicates removal Balancing (so there are as many texts of each sentiment) Stripping (remove any leading and trailing white spaces and new lines) URL removal Contractions Expansion (e.g. converting "it's" to "it is") Shuffling This dataset still needs some data cleaning operations:

Fix special characters (display '&' instead of "&") Remove HTML tags (like "<br>") Translate all text to english (some texts are in other languages, but only a few) Also, note that emojis are present in some texts. I let you decide if you want to process them for your sentiment analysis.

This dataset is the cleaned concatenation of multiple finance news sentiments datasets:

https://www.kaggle.com/datasets/yash612/stockmarket-sentiment-dataset https://www.kaggle.com/datasets/borhanitrash/twitter-financial-news-sentiment-dataset https://www.kaggle.com/datasets/sidarcidiacono/news-sentiment-analysis-for-stock-data-by-company https://www.kaggle.com/datasets/ankurzing/sentiment-analysis-for-financial-news Thanks for their work!

CC-BY-NC

Original Data Source: Finance News Sentiments