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Linguistic Markers in Individuals With Symptoms of Depression in Bi-Multilingual Context
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Author(s): Anbu Savekar (National Institute of Technology Raipur, India), Shashikanta Tarai (National Institute of Technology Raipur, India)and Moksha Singh (National Institute of Technology Raipur, India)
Copyright: 2019
Pages: 25
Source title:
Early Detection of Neurological Disorders Using Machine Learning Systems
Source Author(s)/Editor(s): Sudip Paul (North-Eastern Hill University Shillong, India), Pallab Bhattacharya (National Institute of Pharmaceutical Education and Research (NIPER) Ahmedabad, India)and Arindam Bit (National Institute of Technology Raipur, India)
DOI: 10.4018/978-1-5225-8567-1.ch012
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Abstract
Depression has been identified as the most prevalent mental disorder worldwide. Due to the stigma of mental illness, the population remains unidentified, undiagnosed, and untreated. Various studies have been carried out to detect and track depression following symptoms of dichotomous thinking, absolutist thinking, linguistic markers, and linguistic behavior. However, there is little study focused on the linguistic behavior of bilingual and multilingual with anxiety and depression. This chapter aims to identify the bi-multilingual linguistic markers by analyzing the recorded verbal content of depressive discourse resulting from life situations and stressors causing anxiety, depression, and suicidal ideation. Different contextual domains of word usage, content words, function words (pronouns), and negative valance words have been identified as indicators of psychological process affecting cognitive behavior, emotional health, and mental illness. These findings are discussed within the framework of Beck's model of depression to support the linguistic connection to mental illness-depression.
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