Motor behavior and autism: thematic mapping dataset

Its primary objective is to systematically organize and synthesize existing research to inform evidence-based motor interventions and to identify critical gaps in the field. The dataset comprises curated metadata and thematic classifications derived from 1,215 peer-reviewed articles published between 1994 and 2024.

Articles were analyzed using natural language processing techniques, specifically Latent Dirichlet Allocation (LDA), to uncover and model latent topics. Each topic is annotated with its most frequent terms, associated thematic domains, and core conceptual categories. Manual validation and coding procedures were applied to ensure greater interpretability and analytical rigor.