@inproceedings{wendt-etal-2025-linguistic,
title = "Linguistic Analysis of Veteran Job Interviews to Assess Effectiveness in Translating Military Expertise to the Civilian Workforce",
author = "Wendt, Caroline J. and
Nirjhar, Ehsanul Haque and
Chaspari, Theodora",
editor = "Ebrahimi, Abteen and
Haider, Samar and
Liu, Emmy and
Haider, Sammar and
Leonor Pacheco, Maria and
Wein, Shira",
booktitle = "Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 4: Student Research Workshop)",
month = apr,
year = "2025",
address = "Albuquerque, USA",
publisher = "Association for Computational Linguistics",
url = "https://preview.aclanthology.org/fix-sig-urls/2025.naacl-srw.34/",
pages = "343--355",
ISBN = "979-8-89176-192-6",
abstract = "The ways in which natural language processing (NLP) can inform how veterans can improve effectiveness in translating military experience to workforce utility is underexplored. We design NLP experiments to evaluate the degree of explanation in veteran job interview responses as a proxy for perceived hireability. We examine linguistic and psycholinguistic features, context, and participant variability to investigate the mechanics of effective communication in employee selection. Results yield good performance when distinguishing between varying degrees of explanation in responses using LIWC features, indicating robustness of linguistic feature integration. Classifying Over- and Under-explained responses reflects challenges of class imbalance and the limitations of tested NLP methods for detecting subtleties in overly verbose or concise communication. Our findings have immediate applications for assistive technologies in job interview settings, and broader implications for enhancing automated communication assessment tools and refining strategies for training and interventions in communication-heavy fields."
}
Markdown (Informal)
[Linguistic Analysis of Veteran Job Interviews to Assess Effectiveness in Translating Military Expertise to the Civilian Workforce](https://preview.aclanthology.org/fix-sig-urls/2025.naacl-srw.34/) (Wendt et al., NAACL 2025)
ACL