Novel Transformer Based Contextualized Embedding and Probabilistic Features for Depression Detection From Social Media-Reference-Cited by-同舟云学术

Novel Transformer Based Contextualized Embedding and Probabilistic Features for Depression Detection From Social Media

Published:2024 Issue: Volume:12 Page:54087-54100
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Abbas Muhammad Asad¹,Munir Kashif¹^ORCID,Raza Ali²^ORCID,Samee Nagwan Abdel³^ORCID,Jamjoom Mona M.⁴^ORCID,Ullah Zahid⁵^ORCID

Affiliation:

1. Institute of Information Technology, Khwaja Fareed University of Engineering & Information Technology, Rahim Yar Khan, Pakistan

2. Department of Software Engineering, University of Lahore, Lahore, Pakistan

3. Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P. O. Box 84428, Riyadh, Saudi Arabia

4. Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

5. Department of Information System, King Abdulaziz University, Jeddah, Saudi Arabia

Funder

Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10496991.pdf?arnumber=10496991

Reference32 articles.

1. Text-based Depression Detection on Social Media Posts: A Systematic Literature Review

2. Early depression detection in social media based on deep learning and underlying emotions

3. DepressionNet: A novel summarization boosted deep framework for depression detection on social media;Zogan;arXiv:2105.10878,2021

4. Analysis of Deep Learning Techniques for Early Detection of Depression on Social Media Network - A Comparative Study

5. A profile-based sentiment-aware approach for depression detection in social media

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