ItemBook Chapter

Leveraging social media and natural language processing for early detection of depressive disorders

Title
Leveraging social media and natural language processing for early detection of depressive disorders
Creator
Rajendran, Rajesh Kanna; Kokila, S.S.; Joy, Helen K.; Varghese, Nisha; Sridevi, R.; Cynthia, T.; Blessing, N. R. Wilfred; Ananth, K. J. Paulraj
Description
Depression is a prevalent mental health disorder impacting over 280 million people worldwide, according to recent World Health Organization (WHO) estimates. It poses a substantial burden on individuals and societies, emphasizing the need for early detection and timely intervention. Despite the availability of treatment options, many affected individuals do not seek professional help due to barriers such as stigma, lack of awareness, and insufficient access to mental health services. With the widespread adoption of social media, people increasingly share their thoughts, feelings, and daily experiences online, providing an abundant source of user-generated content. This information can be harnessed to detect early signs of depression. In recent years, advancements in Natural Language Processing (NLP) and Machine Learning (ML) have paved the way for innovative approaches to analyzing social media data for mental health insights. By processing text-based content from platforms such as Twitter, Facebook, and Reddit, NLP techniques can identify linguistic patterns. 2025 by IGI Global Scientific Publishing. All rights reserved.
Source
Demystifying the Role of Natural Language Processing (NLP) in Mental Health;pp.199-219
Date
01-01-2025
Publisher
IGI Global
Coverage
Rajendran R.K., Christ University, India; Kokila S.S., Vellalar Collge for Women, India; Joy H.K., Christ University, India; Varghese N., Christ University, India; Sridevi R., Christ University, India; Cynthia T., Christ University, India; Blessing N.R.W., University of Technology and Applied Sciences, Ibri, Oman; Ananth K.J.P., SKP Arts and Science College, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 979-836934204-6; 979-836934203-9;
Format
online
Language
English
Type
Book chapter

Citation

Rajendran, Rajesh Kanna; Kokila, S.S.; Joy, Helen K.; Varghese, Nisha; Sridevi, R.; Cynthia, T.; Blessing, N. R. Wilfred; Ananth, K. J. Paulraj, “Leveraging social media and natural language processing for early detection of depressive disorders,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 20, 2026, https://archives.christuniversity.in/items/show/24958.

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