Presentation Schedule


Haruki Murakami’s Novels as a Predictive Text and a Data-Driven Approach of Hikikomori Effects on Tertiary-level Students from South India (93025)

Session Information: Student Support and Well-being
Session Chair: Liene Briede

Friday, 13 June 2025 12:15
Session: Session 2
Room: Room 109 (1F)
Presentation Type:Oral Presentation

All presentation times are UTC + 2 (Europe/Paris)

Hikikomori, extreme social withdrawal, poses a considerable issue for young adults worldwide arising from multiple factors, including familial conflict, harassments and various sociological influences that heighten stress levels. New Historicism is used to analyse a prolific Japanese author known for his unique narrative style - Haruki Murakami's works, as predictive texts in the contemporary global context. It further identifies key contributing factors and organises this phenomenon’s effects on students into five distinct stages, while also classifying four levels and typologies of Hikikomori, building on existing research in the field. The study employs a quantitative survey using the DASS21 questionnaire, targeting approximately 300 tertiary students in South India to identify factors associated with the emergence of Hikikomori. The analysis is validated through Structural Equation Modelling via SmartPLS software. The assessment of mental health is concentrated on three key stressors: familial issues, academic pressures and societal conformity. Additionally, Natural Language Processing in Python is used to suggest Murakami’s works as predictive texts. This research serves as a vital resource for stakeholders, including parents, educators, academic institutions and the government, to facilitate the early identification and prevention of individuals susceptible to becoming hikikomori. Furthermore, it may be helpful to propose coping strategies for those already experiencing significant levels of depression, anxiety and stress associated with hikikomori. The study also positions Murakami’s literary works as relevant predictive texts for this phenomenon. Eventually, it aims to enhance societal well-being in alignment with Sustainable Development Goal 3, which advocates for health and well-being for all.

Authors:
Sowndharya T R, SASTRA Deemed University, India
Abirami Kanagarajan, SASTRA Deemed University, India
Suganthi P, SASTRA Deemed University, India


About the Presenter(s)
Dr Abirami, Assistant Professor in SASTRA Deemed University, India. Her research interests are Narratology, Literary Stylistics and ELT. She has received prestigious fellowships and grants. Besides, she has many publications and co-authored books.

Connect on Linkedin
https://www.linkedin.com/in/abirami-kanagarajan-b52336b5

Connect on ResearchGate
https://www.researchgate.net/profile/Abirami-Kanagarajan

Additional website of interest
https://scholar.google.com/citations?user=jhvGO5AAAAAJ&hl=en

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Posted by Clive Staples Lewis

Last updated: 2023-02-23 23:45:00