Linguistic Characteristics of Combat Post-Traumatic Stress Disorder in a Trauma Related Narrative: Computational Context-Aware Approach
These days, an increased prevalence of post-traumatic stress disorder (PTSD) and severe depression has been reported in populations exposed to war. This paper introduces using linguistic analysis of trauma narratives in the context of the study of post-traumatic stress disorder of combatants. As a subject of the analysis, posts of people who participated in combat, obtained from topic-related discussion boards were used. The approach utilizes vocabulary adaptation in NLP using the pre-trained language BERT model in addition to descriptive statistics obtained from text. The novelty of the research lies in the use of a context-sensitive model, while most of the existing research in this area is based on statistical models that use statistical inference to discover hidden patterns.
PTSD, combat, content analysis, linguistic analysis, BERT, linguistic features, anomaly detection, context-aware models
Didushok V. Linguistic Characteristics of Combat Post-Traumatic Stress Disorder in a Trauma Related Narrative: Computational Context-Aware Approach / Valeriia Didushok, Nina Khairova // Computational linguistics and intelligent systems, 22-23 April 2021, Kharkiv. — Lviv ; Kharkiv, 2021. — Vol Vol. II : Proceedings of the 5th International conference, COLINS 2021, Workshop, Kharkiv, Ukraine, April 22-23. — P. 110–112.