AUTHOR=Mehra Vaibhav , Shukla Unmesh , Aggarwal Nitisha , Pundir Amit , Saxena Geetika Jain , Singh Sanjeev 

TITLE=Consistency in verbal expression of death row criminals: concluding life with emotions

JOURNAL=Frontiers in Computer Science

VOLUME=Volume 6 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/computer-science/articles/10.3389/fcomp.2024.1463692

DOI=10.3389/fcomp.2024.1463692

ISSN=2624-9898

ABSTRACT=There is a lack of both data and, more significantly, computational analyses of the linguistic behavior near an individual's final moments of life. The present study proposed a novel machine learning based pipeline, using elements of semantic similarity (BERT and transformers) and emotion extraction in collaboration, to analyze the final statements of death row inmates to understand the consistency in their verbal expression moments before their death. It aimed to reduce human bias and save time in psycholinguistic studies by providing data-backed insights.A new method of analysis was proposed in this study to explore the notions inherent in the statements. A large database of 466 final statements from death row inmates in Texas was utilized in this study. Manual notion analysis was validated by a computational method of notion inferencing. Basic emotions of Anger and Fear majorly dominated the statements, constituting 54% of whole, while 21% of all statements where of emotional states of Happiness and Serenity.The outcomes of this study are expected to contribute to psychological analyses of humans, moments before death, and provide insights to criminology researchers to formulate better strategies of rehabilitation and debate the death penalty.