ORIGINAL RESEARCH article
Front. Artif. Intell.
Sec. Natural Language Processing
Volume 8 - 2025 | doi: 10.3389/frai.2025.1669542
Psycholinguistic Analysis of Text Evidence: Identifying Persons of Interest through Deception, Emotion, and Subjectivity Cues
Provisionally accepted
- Norwich University, Northfield, United States
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Psycholinguistics is an interdisciplinary area of research that bridges elements of linguistics with 4 various branches of psychology. One of its goals is to identify and explain the links that exist 5 between our psyche and the language we speak. In this research we are expanding upon previous 6 research that we did using several different Natural Language Processing (NLP) techniques to 7 identify persons of interest from a scenario that was generated by a large language model (LLM). 8 We successfully identified the guilty parties from the fictional murder case using a combination of 9 Latent Dirichlet Allocation, word vectors, and pairwise correlations. That dataset was smaller and 10 somewhat limited in scope. This research was larger in scope, number of potential suspects, and 11 in the diversity of the corpus used. We used a different approach to this topic, which allowed us to 12 develop a more nuanced method of reverse engineering and breaking down the psycholinguistic 13 features of each suspect. Through the application of n-grams paired with deception, emotion, 14 and subjectivity over time, we were able to identify and measure cues that can be used to better 15 identify persons of interest from a larger pool of candidates.
Keywords: Artificial intelligence (AI), Criminology, digital forensics, natural language processing (NLP), sentiment analysis
Received: 19 Jul 2025; Accepted: 23 Sep 2025.
Copyright: © 2025 Adkins, Al Bataineh and Khanal. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Ali Al Bataineh, aalbatai@norwich.edu
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