Roufaida-ELFANI/Airbnb-Listings-Analysis-Algeria

# 🏠 Airbnb Market Analysis in Algeria 🌍 This project dives into the short-term rental market in Algeria, leveraging data analysis and machine learning techniques to uncover insights into Airbnb listings, guest preferences, and market trends. The goal is to provide actionable insights for hosts, guests, and stakeholders using data-driven approaches. # 📌 Project Overview The project combines data scraping, cleaning, analysis, and machine learning to explore various aspects of Airbnb listings in Algeria. It provides insights into price distributions, guest satisfaction, popular locations, and more through interactive visualizations and advanced modeling techniques. # 🚀 Key Features **Data Analysis** * Pricing Analysis: Examined price distributions, identified outliers, and factors influencing pricing. * Host Performance: Compared metrics for Superhosts vs. Non-Superhosts. * Guest Preferences: Analyzed guest reviews using sentiment analysis to uncover satisfaction drivers. * Trend Identification: Grouped listings to reveal market trends and competitive gaps. **Machine Learning** * XGBoost: Identified the most critical factors influencing pricing and ratings. * KMeans Clustering: Segmented listings by price, ratings, and properties to uncover market patterns. * NLP: Used VADER sentiment analysis and word clouds to extract key themes from guest reviews. **Visualization** Interactive Dashboards: Designed in Power BI to display pricing trends, location-based insights and host performance metrics. # 📊 Key Insights * Distribution of pricing and factors affecting them. * Popular provinces and cities based on reviews and ratings. * Drivers of high guest ratings and satisfaction. * Host performance comparisons. * Themes of guest satisfaction and complaints extracted from reviews.