There are profound differences within the nonprofit sector, and research benefits from the ability to group nonprofits by substantive focus. Researchers typically rely on the National Taxonomy of Exempt Entities (NTEE) codes to categorize nonprofits, but we argue that mission statement text offers a better information source for nonprofit researchers to create categories of organizations. Harnessing advances in data availability and machine-reading technology, this article introduces a new method whereby mission statement analysis drives research and analysis of “like” organizations. Using an automated dictionary method to analyze mission statements, we draw a sample of housing and shelter nonprofits in Washington State. Compared with the corresponding sample based on NTEE classification, our results find roughly double the number of housing and shelter nonprofits based on their mission statements. Our method also proves more accurate than NTEE codes when applied to a sub-sample of nonprofits known to provide shelter for the homeless.
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