These projects will use computational linguistics to study how ideas about organizing the nonprofit and public sector vary over time and across places. The first project is a mixed-methods investigation into the fact that nonprofit organizations are increasingly managed by professionals, who tend to make use of tools that are common in the for-profit sector. The first problem that will be addressed is the facts that the way nonprofits are categorized by the IRS is inconsistent. The second part of the project is to determine to what degree an organization uses for-profit practices without relying on expensive survey or interview data. It will compare web pages to the language of social movements, for-profit, and public organizations using natural language processing. The goal is to create a stand-alone computational model that classifies nonprofits based on characteristics that are not easily accessible otherwise.
The second project is an investigation into how city administrations describe the goals and activities of urban development. I will examine the diffusion of the idea that urban development has to be environmentally sustainable. The goal is to determine the degree to which global climate change and sustainability play a role on the web pages of urban planning departments. The computed probability that a city’s webpage reflects the sustainability paradigm serves as a unique dependent variable in explaining the diffusion of ideas. The idea is that cities with stronger ties to international organizations and INGOs are more likely to bring up sustainability in their urban development discourse. This work will help to explain how abstract ideas travel across the world and become implemented locally.
