The development of AI-driven geolocation technology is important for applications in business, sustainable development, education, and other fields. This study introduces a geolocation framework utilizing social media data from platforms like Twitter, Instagram, and YouTube. Despite the challenge that only 1% to 3% of tweets are georeferenced, our framework employs Boolean queries, geocoding tools, and stochastic models to accurately infer user locations. This automated process handles data extraction, validation, preparation, and model training, ensuring efficiency and consistency. The model achieves high accuracy, particularly in predicting major U.S. cities, and offers a scalable solution for converting ambiguous social media data into actionable insights, supporting informed decision-making across various sectors.