Accomplishments
Facilitating Stock Recommendations through Sentiment Analysis
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Category
Articles
Authors
Shlok Bhura, Tanish B & Kavita Kelkar
Publisher
Ieee Explore
Publishing Date
01-Nov-2024
volume
-
Issue
-
Pages
-
- Abstract
focused on developing a sentiment analysis model to enhance the accuracy of stock recommendations by analyzing investor sentiment derived from news articles and social media feeds. By integrating real-time stock data from YFinance and applying sentiment analysis tools like VADER and TextBlob, I was able to classify stocks with actionable insights—Buy, Sell, or Hold.
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