Mining real estate data: A systematic review of text-based approaches
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Department of Real Estate and Investment Economics, Krakow University of Economics, Poland
Submission date: 2025-02-13
Final revision date: 2025-06-17
Acceptance date: 2025-07-04
Corresponding author
Joanna Wegrzyn
Department of Real Estate and Investment Economics, Krakow University of Economics, Poland
HIGHLIGHTS
- text mining procedure and techniques
- topci modelling
- sentiment anayslis
- systematic literature reviw (SLR)
KEYWORDS
TOPICS
ABSTRACT
The rise of Big Data has transformed information processing, with text mining techniques gaining prominence across various disciplines, including real estate market analysis. The research aim is to provide a comprehensive overview of this field, highlighting emerging trends and potential areas for future research. To explore the application of text mining approaches, the study presents a systematic literature review (SLR) combining performance analysis, science mapping techniques and topic modeling. The analysis reveals a noticeable increase in research activity post-2015. Key application areas of text mining techniques include housing and real estate markets, urban planning and social media, smart cities and public spaces, online reviews and consumer feedback, and sustainable development. Additionally, the research identifies challenges related to data quality, standardization, and computational efficiency. The study concludes by identifying future research directions and potential applications for real estate practice.
FUNDING
This work was supported by the Krakow University of Economics, Poland [PRW/WPOT/2024/0038].