Analysis of Real Estate Market Pricing Rules and Construction of Prediction Model from the Perspective of Big Data

Amidst the digital revolution, data resources are surging exponentially. Cutting-edge technologies like big data and AI are rapidly evolving, creating new opportunities for industries. Yet, the real estate market is becoming more complex and unstable. Frequent policy changes, supply-demand imbalances, and economic volatility are heightening industry uncertainty. Meanwhile, consumers are demanding better living experiences, smarter amenities, and greener homes. These diverse and refined needs are driving a major shift in the real estate landscape. This paper employs a method of literature review and case study. It investigates the influence of big data in the prediction of price and the construction of the real estate market. This big data analysis on housing prices holds significant value by empowering homebuyers to understand explicit/implicit factors for informed decisions, guiding real estate firms on land/pricing strategies, supporting government policy formulation with data, aiding macroeconomic stability through risk identification in price patterns, and enriching academic theory in real estate economics through systematic analysis and novel methods.