Building an Automated Stock Sentiment Analysis Dashboard with Streamlit, NewsAPI, and Llama 3 Integration: Generating Real-time Investment Insights

Are you struggling to make stock investment decisions? This article guides you through building an automated dashboard using Streamlit to fetch real-time news data from NewsAPI and perform sentiment analysis on those news articles via Llama 3 to support your investment decisions. This enables you to make quick, data-driven investment choices.

1. The Challenge / Context

The stock market is constantly changing, and making investment decisions amidst a flood of information is extremely challenging. It's difficult to predict the future based solely on past stock price data; a comprehensive analysis of various news articles, social media opinions, and more is required. However, manually analyzing such information is time-consuming, labor-intensive, and difficult to maintain objectivity. In particular, to seize short-term investment opportunities, real-time sentiment analysis of evolving news is essential. The fundamental problem is the lack of tools for individual investors to perform such analysis efficiently.

2. Deep Dive: Llama 3

Llama 3 is a state-of-the-art large language model (LLM) developed by Meta. It offers significantly more powerful performance than previous models, particularly excelling in areas such as natural language understanding, generation, translation, and conversation. Llama 3 can be utilized to analyze text data and determine positive, negative, or neutral sentiment.