An attention-based CNN-BiLSTM model for depression detection on social media text

Author:

Philip Thekkekara JoelORCID,Yongchareon SiraORCID,Liesaputra Veronica

Publisher

Elsevier BV

Reference57 articles.

1. Predicting depression levels using social media posts;Aldarwish,2017

2. AlSagri, H. S., & Ykhlef, M. (2020). Machine Learning-based Approach for Depression Detection in Twitter Using Content and Activity Features. arXiv preprint arXiv:2003.04763.

3. Bahdanau, D., Cho, K., & Bengio, Y. (2014). Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473.

4. The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations;Baron;Journal of Personality and Social Psychology,1986

5. Beck, A., Rush, A., Shaw, B., & Emery, G. (1979). Cognitive therapy of depression. Guilford Press. New York.

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3. Early depression detection using ensemble machine learning framework;International Journal of Information Technology;2024-06-12

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