Taxonomy Granularity Affects Detection Tool Effectiveness
Categories with more granular type definitions enable more precise detection rules. In dark pattern research, “Interface Interference” contains 32% of all types and shows the most mature detection coverage. Categories like “Nagging” and “Obstruction” have fewer subtypes and correspondingly less detection tool support.
The relationship runs both directions: detailed classification enables better detection, but detection tools also tend to drive further taxonomic refinement in the categories they address.
This creates a reinforcing cycle where well-studied categories get better tools, which produces more data, which enables finer classification, while understudied categories remain coarse.
Related: 05-atom—detection-coverage-gap, 07-molecule—taxonomy-to-detection-gap