Topic Modeling

A machine learning technique that automatically discovers abstract themes or topics within a collection of documents by analyzing patterns of word co-occurrence. Latent Dirichlet Allocation (LDA) is the most widely used topic modeling algorithm. In accessibility research, topic modeling can be applied to large datasets of user-generated content—such as social media posts, forum discussions, or product reviews—to identify the key themes and concerns that people with disabilities discuss, providing scalable insights that complement traditional qualitative research methods like interviews and focus groups.