Detecting signs of depression on social media: A machine learning analysis and evaluation

This publication has 60 references indexed in Scilit:

• Leveraging web scraping and stacking ensemble machine learning techniques to enhance detection of major depressive disorder from social media posts
  Social Network Analysis and Mining, 2024
• Detecting depression tendency with multimodal features
  Computer Methods and Programs in Biomedicine, 2023
• Automatic depression score estimation with word embedding models
  Artificial Intelligence in Medicine, 2022
• An hybrid deep learning approach for depression prediction from user tweets using feature-rich CNN and bi-directional LSTM
  Multimedia Tools and Applications, 2022
• Explainable depression detection with multi-aspect features using a hybrid deep learning model on social media
  World Wide Web, 2022
• Automatic detection of depression symptoms in twitter using multimodal analysis
  The Journal of Supercomputing, 2021
• Machine learning and deep learning
  Electronic Markets, 2021
• Depression and anorexia detection in social media as a one-class classification problem
  Applied Intelligence, 2021
• Multimodal depression detection on instagram considering time interval of posts
  Journal of Intelligent Information Systems, 2020
• Multi-kernel SVM based depression recognition using social media data
  International Journal of Machine Learning and Cybernetics, 2017