Real-estate public expectation big data processing method and system

Abstract

The invention discloses a real-estate public expectation big data processing method. The real-estate public expectation big data processing method includes the steps of on the basis of big data, building an emotion dictionary of a real estate market; through a web crawler, obtaining original data; cleaning and screening the original data; according to a keyword database and a real-estate public emotion analysis database, building a real-estate public expectation training model; through a web crawler, obtaining data to be processed; inputting the data to be processed to the training model to train the data to be processed; classifying the data to be processed, building real-estate public expectation indexes, and predicting the correlation between the real estate big data and the real-estatepublic expectation indexes. The real-estate public expectation big data processing method has the advantages that the correlations between the real-estate public expectation indexes and different media and the correlations between the real-estate public expectation indexes and different organizations are predicted in real time. Data analysis on all samples is achieved at an objective and intact perspective, different organizations and different media are fully focused, and real-estate public expectation differences among different organizations and real-estate public expectation differences among different media are analyzed meticulously and professionally.

Description

technical field [0001] The invention relates to the technical field of big data processing, in particular to a method and system for processing real estate public expectations big data. Background technique [0002] At present, the background of the real estate industry mainly includes the following aspects: [0003] (1) Uncertainty and complexity of external environmental factors: The adjustment of public expectations will further affect the volatility of the real estate market. The greater the uncertainty, the more severe the market volatility caused by expectations will be. Existing literature mostly uses extrapolation methods and econometric models to measure real estate public expectations, and a small part uses statistical survey methods. However, these measurement indicators are limited by data availability, and generally the update frequency is not high. Public expectations are characterized by high elasticity and instability, and the real-time requirements for thei...

AI Technical Summary

Problems solved by technology

Existing literature mostly uses extrapolation methods and econometric models to measure real estate public expectations, and a small part uses statistical survey methods, but these measurement indicators are limited by data availability, and generally the update frequency is not high

Public expectations are characterized by large elasticity and instability, and the real-time requirements for their measurement indicators are high, which cannot be effectively measured

Most of the existing research is based on the framework of adaptive expectations or rational expectations, assuming that economic subjects are completely rational, and seldom considers the role of irrational factors on the formation and impact of expectations, which is not conducive to the effective management of public expectations

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