# GSE Sentiment Analysis & Stock Prediction System
A comprehensive research platform for analyzing investor sentiment and predicting stock movements on the Ghana Stock Exchange (GSE) using advanced machine learning, natural language processing, and predictive analytics techniques.
## 🌐 Live Deployment
**Access the GSE Sentiment Analysis System at:**
**
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*Real-time sentiment analysis and stock prediction platform for Ghanaian investors and researchers.*
## 📖 Table of Contents
- Overview
- Development Process
- Quick Start
- System Architecture
- Data Sources & Companies
- Features & Capabilities
- Usage Examples
- Dashboard Guide
- Research Methodology
- Troubleshooting
- Contributing
## 🎯 Overview
This system implements a **hybrid automated-manual sentiment analysis framework** for the Ghana Stock Exchange, addressing the research gap in applying machine learning to emerging market investment decisions. The platform combines:
- **13 data sources** including news websites, social media, and manual expert input
- **5 sentiment analysis methods** (VADER, TextBlob, Lexicon, Hybrid, Advanced BERT)
- **12 machine learning algorithms** for price movement prediction
- **Real-time processing** with 70-75% prediction accuracy
- **Interactive research dashboard** for analysis and validation
**Key Achievement:** Establishes Granger causality between sentiment and price movements in 8/16 GSE companies, demonstrating the predictive power of sentiment-based analysis in emerging markets.
## 🛠️ Development Process
### Phase 1: Research Foundation (Weeks 1-2)
- Literature review of behavioral finance and sentiment analysis
- Analysis of GSE market characteristics and data availability
- Design of multi-source data collection framework
### Phase 2: Core System Development (Weeks 3-6)
- Implementation of sentiment analysis pipeline (VADER, TextBlob, BERT)
- Development of web scraping infrastructure for Ghanaian news sources
- …