Idiolectic Models for Diagnostics: A Novel Approach to Understanding Semantic Relationships in Clinical Populations

Resumen

This study presents a novel method, Idiolectic Models for Diagnostics, to analyze and understand unique semantic relationships in clinical populations. The initial paper presents the methodological foundation for the Idiolectic Models for Diagnostics, with subsequent papers focusing on clinical populations. Our method aims to elucidate personal idiolectic connections, providing a deeper understanding of the semantic landscape within and between individuals. This study analyzed group-level differences in the text of forum posts on a popular social media site and individual-level idiolect comparisons in OCD populations compared to more general population. Our results demonstrate significant differences in the semantic associations with the word "attract" between OCD users and general users. Specifically, OCD users exhibited more varied and less consistent associations, reflecting the diverse nature of their obsessions and compulsions, while general users showed more stable and uniform associations. Additionally, group-level comparisons between art and programming subgroups revealed significant differences in semantic distances in associations with the word “abstract,” indicating distinct word usage patterns across communities. These findings highlight the potential of Idiolectic Models for Diagnostics in uncovering meaningful differences in semantic relationships within clinical populations and online communities, both at group- and individual-level.

Áreas y palabras clave

Cómo citar (APA 7)

Witmer, K. M., & Brick, T. R. (2025). Idiolectic Models for Diagnostics: A Novel Approach to Understanding Semantic Relationships in Clinical Populations. https://doi.org/10.31234/osf.io/fd7ba_v2