Artificial Intelligence Adoption in Housing: A Bibliometric Analysis

This study examines the academic field of Artificial Intelligence in Housing by examining the publications and indexed documents in Scopus and web of science (WOS) from 2000 to 2024. Consequently, we examined the publishing trends, exemplary articles, and the most engaged participants and funding institutions in the domain of AI and Housing research. A bibliometric analysis was performed to examine the network of co-authorships, keywords, and citations in the domain of AI and Housing research. The Scopus and WOS search resulted in the discovery of 246 related publications on AI and Housing. With an increase from 1 publication to 68 publications within the observed years. Additionally, trends analysis indicated a significant increase of 5,016 in publications between 2000 and 2024. Articles are the most often utilized document type, including 172 of the overall amounts. The most prolific researchers in the field of AI and Housing are Ahmad, Chatterjee, Cho, Lee, Mehmood, Shaheen, Yang, and Zhao. All having published 3 documents each. Additionally, ten institutions have produced the highest number of published documents. The output of the affiliations active in the topic is primarily attributed to the funding, specifically the National Science Foundation, which is the leading funding institution based in the United States and has contributed to 8 publications. An analysis of keyword co-occurrence revealed 4 main study areas that cover the essential tools, theories, methodologies, and socioeconomic and financial aspects of artificial intelligence and Housing. Future research in the field of artificial intelligence and Housing will focus on employing sophisticated machine learning, and neural network algorithms to precisely predict Housing transactions patterns while further enhancing housing market transactions across countries.