Paper Details

Name: Pragya Rajput, Pradeep Kumar Reddy Chereddy, Vaishnavi Yampalla, Sai Sreekar Devoju, Keshav & Vinay Raparthi
Country: India

Year: 2026
Volume: Volume No: 13, January, Year: 2026 (Special Issue)
Page Number: 481-488
DOI: https://doi.org/10.5281/zenodo.19063217

ABSTRACT –
The widespread use of social media platforms has provided new avenues for understanding and taking action on mental health, with a focus on depression on a person’s level of state. Over the past few years, researchers and mental health care professionals have increasingly leveraged artificial intelligence (AI) and natural language processing (NLP) techniques to build automated systems that can detect signals of depression among social media users. In this paper, we provide a detailed overview of the existing state-of-the-art methods in AI-based depression detection using a range of techniques: linguistic, sentiment analysis, and machine learning methods. We critique existing approaches with attention to their strengths and weaknesses and touch on the ethical implications of automated depression detection systems. In addition, we discuss future research directions for improving the accuracy and reliability as well as the ethical aspect of AI-based depression detection on social
media platforms with particular emphasis on privacy protection and handling algorithmic bias in AI algorithms. We research the topic to advance our understanding of the ways in which artificial intelligence(AI) may be used to support and help in mental health on the internet.

Index Terms — Depression, Social Media, Artificial Intelligence, Natural Language Processing.