Investigating machine learning & natural language processing techniques applied for predicting depression disorder from online support forums: A systematic …

IA Nanomi Arachchige, P Sandanapitchai… - Information, 2021 - mdpi.com
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 …

Depression detection from social networks data based on machine learning and deep learning techniques: An interrogative survey

KM Hasib, MR Islam, S Sakib, MA Akbar… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Users can interact with one another through social networks (SNs) by exchanging
information, delivering comments, finding new information, and engaging in discussions that …

Screening internet forum participants for depression symptoms by assembling and enhancing multiple NLP methods

C Karmen, RC Hsiung, T Wetter - Computer methods and programs in …, 2015 - Elsevier
Depression is a disease that can dramatically lower quality of life. Symptoms of depression
can range from temporary sadness to suicide. Embarrassment, shyness, and the stigma of …

[Retracted] Psychological Analysis for Depression Detection from Social Networking Sites

S Gupta, L Goel, A Singh, A Prasad… - Computational …, 2022 - Wiley Online Library
Rapid technological advancements are altering people's communication styles. With the
growth of the Internet, social networks (Twitter, Facebook, Telegram, and Instagram) have …

Improving mental health classifier generalization with pre-diagnosis data

Y Liu, L Biester, R Mihalcea - … of the International AAAI Conference on …, 2023 - ojs.aaai.org
Recent work has shown that classifiers for depression detection often fail to generalize to
new datasets. Most NLP models for this task are built on datasets that use textual reports of a …

[HTML][HTML] Detecting and measuring depression on social media using a machine learning approach: systematic review

D Liu, XL Feng, F Ahmed, M Shahid, J Guo - JMIR Mental Health, 2022 - mental.jmir.org
Background: Detection of depression gained prominence soon after this troublesome
disease emerged as a serious public health concern worldwide. Objective: This systematic …

Leveraging domain knowledge to improve depression detection on Chinese social media

Z Guo, N Ding, M Zhai, Z Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Depression is a prevalent and severe mental disorder that often goes undetected and
untreated, particularly in its early stages. However, social media has emerged as a valuable …

Deep learning-based depression detection from social media: Comparative evaluation of ml and transformer techniques

BG Bokolo, Q Liu - Electronics, 2023 - mdpi.com
Detecting depression from user-generated content on social media platforms has garnered
significant attention due to its potential for the early identification and monitoring of mental …

Deep learning for prediction of depressive symptoms in a large textual dataset

MZ Uddin, KK Dysthe, A Følstad… - Neural Computing and …, 2022 - Springer
Depression is a common illness worldwide with potentially severe implications. Early
identification of depressive symptoms is a crucial first step towards assessment, intervention …

Fine-grained depression analysis based on Chinese micro-blog reviews

T Yang, F Li, D Ji, X Liang, T Xie, S Tian, B Li… - Information Processing & …, 2021 - Elsevier
Depression is a widespread and intractable problem in modern society, which may lead to
suicide ideation and behavior. Analyzing depression or suicide based on the posts of social …