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Real estate prices have a significant impact on individuals, families,businesses, and governments. The general objective of real estate priceprediction is to identify and exploit socioeconomic patterns arising from realestate transactions over multiple aspects, ranging from the property itself toother contributing factors. However, price prediction is a challengingmultidimensional problem that involves estimating many characteristics beyondthe property itself. In this paper, we use multiple sources of data to evaluatethe economic contribution of different socioeconomic characteristics such assurrounding amenities, traffic conditions and social emotions. Our experimentswere conducted on 28,550 houses in Beijing, China and we rank eachcharacteristic by its importance. Since the use of multi-source informationimproves the accuracy of predictions, the aforementioned characteristics can bean invaluable resource to assess the economic and social value of real estate.Code and data are available at: https://github.com/IndigoPurple/PATE

PATE: Property, Amenities, Traffic and Emotions Coming Together for Real Estate Price Prediction