Investigating Machine Learning & Natural Language Processing Techniques Applied for Predicting Depression Disorder from Online Support Forums: A Systematic Literature Review

Abstract

Depression is a common mental health disorder that affects an individual’s moods, thought processes and behaviours negatively, and disrupts one’s ability to function optimally. In most cases, people with depression try to hide their symptoms and refrain from obtaining professional help due to the stigma related to mental health. The digital footprint we all leave behind, particularly in online support forums, provides a window for clinicians to observe and assess such behaviour in order to make potential mental health diagnoses. Natural language processing (NLP) and Machine learning (ML) techniques are able to bridge the existing gaps in converting language to a machine-understandable format in order to facilitate this. Our objective is to undertake a systematic review of the literature on NLP and ML approaches used for depression identification on Online Support Forums (OSF). A systematic search was performed to identify articles that examined ML and NLP techniques to identify depression disorder from OSF. Articles were selected according to the PRISMA workflow. For the purpose of the review, 29 articles were selected and analysed. From this systematic review, we further analyse which combination of features extracted from NLP and ML techniques are effective and scalable for state-of-the-art Depression Identification. We conclude by addressing some open issues that currently limit real-world implementation of such systems and point to future directions to this end.

Natural Language Processing Influence on Digital Socialization and Linguistic Interactions in the Integration of the Metaverse in Regular Social Life

“…The deep learning module is an integral component of this process, which deftly interprets the user's language and actions to extract nuanced indications. The system can recognize indicators of stress, anxiety, depression, or other mental health conditions by examining patterns and changes over time [88]. The virtual psychological assistant can then provide customized help because it can forecast the user's mental state based on this analysis.…”

Helicopter parenting through the lens of reddit: A text mining study

“…Recent text mining applications have allowed social scientists to observe natural online behaviour, gaining deeper insights into users’ real-time psychosocial characteristics [ 2 ]. Natural Language Processing (NLP), a subfield of Artificial Intelligence, is an emerging technology that uses machines to understand human languages [ 44 ]. The NLP process comprises the following steps: (a) text preprocessing, in which the dataset is cleaned by removing non-textual information (e.g., emojis, images, and HTML tags); (b) text representation, where the dataset is transformed into word vectors; (c) model training, during which algorithms are utilised to train a model (e.g., sentiment analysis, opinion mining, or topic modeling); and (d) model evaluation, where the model is evaluated to ensure it has optimal generalisability to other corpora [ 45 ].…”

Depression detection in social media comments data using machine learning algorithms

“…A statistical report says, all over the world almost 4.67 billion people are using the internet and searching for information for various reasons [15]. Many types of research are being done on depression detection.…”

“…Smith et al [19] interviewed 387 pregnant women and only 26% were screened for anxiety disorder. Arachchige et al [15] identified 1,335 references from different datasets and used ML and NLP for depression detection. They used Facebook, Twitter, and Reddit forums.…”