A Comparative Study of Deep Learning Methods for Depression Detection in Social Media Data

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Year : 2025 | Volume : 12 | Issue : 03 | Page : 55 65
    By

    Ruchi Jain,

  • Tariq Siddiqui,

  • Ashish Pandey,

  1. Associate Professor, Department of Computer Science and Engineering, Lakshmi Narain College of Technology & Science, Bhopal, Madhya Pradesh, India
  2. Research Scholar, Department of Computer Science and Engineering, Bhabha University, Bhopal, Madhya Pradesh, India
  3. Associate Professor, Department of Computer Science and Engineering, Bhabha University, Bhopal, Madhya Pradesh, India

Abstract

With the rise of social media platforms like Twitter, Reddit, and Facebook, individuals increasingly share personal information about their moods, behaviors, and mental states. This trend provides a unique opportunity to leverage large-scale textual data for understanding and monitoring mental health conditions, particularly depression, a prevalent and challenging mental health issue. Traditional depression assessments are often confined to clinical environments and lack the capacity for real-time monitoring. In contrast, social media provides a continuous, real-time stream of information that could be harnessed for early detection and intervention. This research aims to develop an advanced depression detection model tailored specifically for social media text by utilizing state-of-the-art Natural Language Processing (NLP) and deep learning techniques. Unlike traditional feature engineering-based methods, this study focuses on deep learning frameworks, which can capture nuanced linguistic patterns indicative of depressive symptoms without manual intervention. The research will explore various architectures, including Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM) networks, and Transformer models, incorporating strategies like attention mechanisms, transfer learning, and hybrid approaches to enhance accuracy.

Keywords: Machine learning, deep learning, depression, healthcare, mental health diagnosis

[This article belongs to Journal of Artificial Intelligence Research & Advances ]

How to cite this article:
Ruchi Jain, Tariq Siddiqui, Ashish Pandey. A Comparative Study of Deep Learning Methods for Depression Detection in Social Media Data. Journal of Artificial Intelligence Research & Advances. 2025; 12(03):55-65.
How to cite this URL:
Ruchi Jain, Tariq Siddiqui, Ashish Pandey. A Comparative Study of Deep Learning Methods for Depression Detection in Social Media Data. Journal of Artificial Intelligence Research & Advances. 2025; 12(03):55-65. Available from: https://journals.stmjournals.com/joaira/article=2025/view=217487


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Regular Issue Subscription Review Article
Volume 12
Issue 03
Received 04/02/2025
Accepted 01/07/2025
Published 24/07/2025
Publication Time 170 Days
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