DepressionNet: Learning Multi-modalities with User Post Summarization for Depression Detection on Social Media-Reference-Cited by-同舟云学术

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DepressionNet: Learning Multi-modalities with User Post Summarization for Depression Detection on Social Media

Published:2021-07-11 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval
language:
Short-container-title:

Author:

Zogan Hamad¹,Razzak Imran²,Jameel Shoaib³,Xu Guandong⁴

Affiliation:

1. University of Technology Sydney & College of Computer Science and Information Technology, Sydney, NSW, Australia

2. Deakin University, Geelong, Australia

3. University of Essex, Colchester, United Kingdom

4. University of Technology Sydney, Sydney, NSW, Australia

Funder

Australian Research Council

Global Challenges Research Fund

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3404835.3462938

Reference53 articles.

1. Tuka Al Hanai Mohammad M Ghassemi and James R Glass. 2018. Detecting Depression with Audio/Text Sequence Modeling of Interviews.. In Interspeech. 1716--1720. Tuka Al Hanai Mohammad M Ghassemi and James R Glass. 2018. Detecting Depression with Audio/Text Sequence Modeling of Interviews.. In Interspeech. 1716--1720.

2. Detecting suicidal ideation on forums: proof-of-concept study;Aladaug Ahmet Emre;JMIR,2018

3. Enriching Word Vectors with Subword Information

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