Amal Alqahtani


2022

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A Quantitative and Qualitative Analysis of Schizophrenia Language
Amal Alqahtani | Efsun Sarioglu Kayi | Sardar Hamidian | Michael Compton | Mona Diab
Proceedings of the 13th International Workshop on Health Text Mining and Information Analysis (LOUHI)

Schizophrenia is one of the most disabling mental health conditions to live with. Approximately one percent of the population has schizophrenia which makes it fairly common, and it affects many people and their families. Patients with schizophrenia suffer different symptoms: formal thought disorder (FTD), delusions, and emotional flatness. In this paper, we quantitatively and qualitatively analyze the language of patients with schizophrenia measuring various linguistic features in two modalities: speech and written text. We examine the following features: coherence and cohesion of thoughts, emotions, specificity, level of commit- ted belief (LCB), and personality traits. Our results show that patients with schizophrenia score high in fear and neuroticism compared to healthy controls. In addition, they are more committed to their beliefs, and their writing lacks details. They score lower in most of the linguistic features of cohesion with significant p-values.