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Homeowners associations (HOAs) play a substantial role in housing governance in the United States. While some academic research has been conducted on the content of governingcovenants, conditions, and restrictions (CC&Rs) in common-interest developments (CIDs) with regard to specific topics like landscaping, there has been no work that takes a total approach to examining the purpose of such documents using natural language processing. In this project, I thus answer two main questions: how do HOAs perform local governments’ regulatory role and what policy connotations are expressed in the language used in HOA CC&Rs? Using a public records request, I obtain and then leverage the texts of original CC&R documents from Orange County, Florida and the county's voluntary list of HOAs to construct a text corpus of CC&Rs. I then conduct both text analysis (assessing word frequency/clouds, topic modeling, etc.) and sentiment analysis (e.g. using various lexicon dictionaries to assess if CC&Rs are negative as predicted by their role in regulating communities) in Python to get a comprehensive understanding of the operations of the county's HOAs. Within this analysis, I also assess the difference in language used for different kinds and ages of CIDs. This work has significant policy implications, at a time in which state governments, including Florida, are increasingly regulating HOA boards' activities. Empirical work identiifying the roles HOAs play on a day-to-day basis, as well as the extent to which those procedures are boilerplate across a region/developer, is key to furthering discussion on the normative role such associations should play in the US.