Predictive Paradigm: AI-Driven Social Media Analysis for Real Estate Sales Forecasts

Forecasting sales holds significant importance in the realms of production and supply chain management. It plays a crucial role in shaping a firm’s planning, strategy formulation, marketing endeavors, logistical operations, warehouse management, and overall resource allocation. This paper employs five distinct machine learning (ML) algorithms, i.e., decision tree, random forest, K-nearest neighbors (KNN), K-means, and support vector machine (SVM) to forecast the accuracy percentage of real estate trends on social media platforms. A standard dataset comprising 200 respondents spanning various age groups is utilized. The simulation outcomes encompass predictions of accuracy percentages for heightened awareness, enhanced engagement, accelerated sales, and improved customer services.