Vital-Ahishakiye/Sentiment-Analysis-Rwanda-Public-Transport

# Public Sentiment Analysis on Rwanda's Distance-Based Fare Pricing ## 🚀 Project Overview This project analyzes public sentiment on Rwanda's newly introduced distance-based fare pricing model for public transport. By examining social media comments, I extracted key themes and categorized user feedback into positive, negative, and neutral sentiments. ## 📂 Project Structure - `Executive_Summary.md` — Detailed executive summary with insights and recommendations - `Dataset` — Raw and processed data used for the analysis - `Python Scripts` — Python scripts for data preprocessing, sentiment analysis, and visualization - `Results` — Outputs including word clouds, sentiment scores, and dashboard - `PowerBI_Dashboard.pbix` — Interactive Power BI dashboard visualizing the results ## 📝 Key Insights - Majority of users expressed positive sentiments regarding fair pricing and service improvements. - Negative comments focused on technical issues, overcrowding, and regional disparities. - Neutral comments included inquiries and clarifications about system functionality. ## 🚀 Models Used - **TextBlob:** Rule-based sentiment analysis - **VADER (from NLTK):** Fine-tuned for social media text - **Theme Clustering:** Identified key discussion themes via text clustering ## 🧪 Methodology & Challenges - Initially attempted to use X API to fetch tweets directly but exceeded the free plan limit (100 tweets/month) very early. - Scraped blogs and news but found limited public interaction on this topic. - Final dataset consists of 128 unique replies to two posts (in Kinyarwanda and English) by RURA from early December 2024 announcing the pilot pricing scheme. - Power BI requires a premium subscription to share dashboards publicly; thus, only a PDF version of the dashboard is provided alongside the Power BI project file. ## 💡 How to Use 1. Clone the repository: ```bash git clone [repository_link] ``` 2. Set up your Python environment: ```bash pip install -r requirements.txt ``` 3. Downloa …