Sentiments and Semantics: A Review of the Content Analysis Literature in the Era of Big Data

Abstract Drilling into data to understand property as a financial investment is one of the primary considerations of real estate research. This paper is designed to shed light on some of the newer and more innovative studies by highlighting the use qualitative data and content analysis throughout the literature to enhance our understanding of property. Particular attention is placed on linguistics research including readability metrics, semantic analysis, and sentiment analysis. Ocular tracking is also addressed as a way to evaluate unstructured forms of data. These methods are rigorous enough to be used on their own or as supplements to conventional pricing models, subject to the requirements of the research.