This Python tool automates the process of sentiment analysis for news articles related to a given stock symbol. It utilizes the Natural Language Toolkit (NLTK) to preprocess the text, removing stopwords, and then applies the TextBlob library's NaiveBayesAnalyzer to determine the sentiment of the text. The tool calculates the average sentiment score from multiple news articles to provide an overview of the current sentiment towards a stock.
To run this tool, you will need Python and several dependencies. Install them using the following commands:
pip install nltk textblob requests
python -m textblob.download_corporaMake sure you have an API key from NewsAPI, which you will insert into a .env file within your directory. The .env file should contain:
NEWSAPI_KEY=your_api_key
To analyze the sentiment for a particular stock, run the get_stock_sentiment function with the stock ticker as a string argument. For example:
get_stock_sentiment('TSLA') # Replace 'TSLA' with your target stock tickerThe function will output the average sentiment score for the specified stock based on the fetched news articles.