Decoding Depression: A Psycholinguistic Lexical Analysis of the Urdu Speech
DOI:
https://doi.org/10.53057/linfo/2023.6.1.4Keywords:
linguistic markers of depression, the Urdu language, lexical analysis, Urdu content words, language of depression, automatic detectionAbstract
Depression is one of the most prevalent mental health issues with a significant impact on both individuals and society. This study focuses on identifying linguistic markers of depression in the Urdu speech of Pakistani participants to aid in its early detection. Despite extensive research on linguistic markers of depression in various languages of the world, the Urdu language was still completely unexplored. This study addresses this notable gap by exploring and describing linguistic markers in the Urdu speech of Pakistani participants. Linguistic markers of depression can enable timely intervention by people around affected individuals and support mental health professionals in improving diagnosis and assessment. Additionally, they can aid developers of artificial intelligence in creating tools for automatic detection. This support is important for individuals who, due to internal loss of motivation or external negative social pressures, may not disclose their condition, seek medical help, and continue to suffer silently or even contemplate suicide. In this study, sixty Pakistani Punjabi-Urdu bilinguals, comprising an equal number of depressed and non-depressed participants, were selected using criterion sampling. Through semi-structured interviews, their speech was elicited, manually transcribed, and analysed for both context-independent and context-dependent lexical markers. The analysis revealed significant differences in the use of absolutist, negative emotion, positive emotion, cognitive, religious, and health-related words between the two groups.
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