Abstract: Systems and methods for providing real estate trends and other insights based on a natural language process of text data, including various news sources, to a specified market (e.g., national, local). In some embodiments, the real estate prediction system performs semantic-based analysis to determine a sentiment associated with a source. For example, the real estate prediction system can access an embedding system to generate embeddings for words and phrases contained within a source. These embeddings can be input to an LLM for determination of a general sentiment of the source, or used directly in an LLM. The real estate prediction system perform additional semantic analysis, such as word counting, to classify and organize the content of sources. Based on the generated sentiments, the real estate prediction system can generate predictions, estimations, and other insights relating to the sources.