Mapping Civic Engagement: Methodologies and Insights from the Australian Civic Opportunities Index Project
On behalf of the Scanlon Foundation Research Institute, the Civic Opportunities Index aimed to develop local government authority (LGA)-level estimates of civic opportunities available to Australians, adapting methodologies from de Vries et al.’s (2024) U.S. civic opportunities index. This index classifies organisation-level opportunities for events, membership, volunteering, and taking action. The project utilised a combination of data sources: the Australian Charities and Not-for-profits Commission Charity Register, Annual Information Statement Register, and programs register, as well web-scraped data from non-profit organisations’ websites. Organisational opportunities were predicted from the web-scraped corpus using various machine learning approaches (lasso, random forests, and XGboost). This presentation will explore the various methodologies employed in the project to detect and categorise civic activities. The methodologies include traditional web scraping techniques, the use of large language models (LLMs), and human coding. We also address potential shortcomings and limitations in the work, as well as areas of potential improvement.
