Abstract

Real estate industry is important for national economy. China and the U.S. are the world’s major economies where real estate both plays an important role during the Global Financial Crisis of 2008. Academic paper is the common form to present scholars’ opinions which are usually the most scientific and objective knowledge of a discipline. However, traditional review methods with manual inspection are considered to be time-consuming, subjective and inefficient to process them. A large-scale review gathering systematic data to find academic concerns on real estate is missing. With recent big data technologies, especially the structural topic modeling approach, we make a contribution to the understanding of experts’ views about real estate by analyzing the abstracts of all related academic papers in SCI-EXPANDED, SSCI and CSCD databases. Besides, we compare the topical differences when scholars discuss real estate issues in China and the U.S., respectively. The structural topic model indicates that the data set of the collected 1027 abstracts can be abstracted into 9 topics, which represent the major academic concerns of real estate issues in the two countries. Furthermore, we find that the real estate research of the U.S. focuses more on Financial/Bubbles, Environment/Substance, Credit/Mortgage/Crisis, Causality Test Methods, and Politics/Equality, while China’s studies address more on Urbanization, Rural Real Estate, Commercial Housing, and Foreign Investment/Other Industries. Finally, we analyze the differences of topical prevalence between China and the U.S., and find that the major differences can be derived from distinguishing features of development stage of real estate, the national economy, the stress of connections with finance and effect towards real world, the research methods employed and the political and racial background, in the two countries.

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