SenseMood: Depression Detection on Social Media

Author:

Lin Chenhao1,Hu Pengwei2,Su Hui3,Li Shaochun2,Mei Jing2,Zhou Jie3,Leung Henry4

Affiliation:

1. Xi'an Jiaotong University, Xi'an, China

2. IBM Research, China, Beijing, China

3. Wechat AI & Tencent Inc., Beijing, China

4. University of Calgary, Calgary, AB, USA

Publisher

ACM

Cited by 92 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Language Models for Online Depression Detection: A Review and Benchmark Analysis on Remote Interviews;ACM Transactions on Management Information Systems;2024-08-13

2. Automatic depression prediction via cross-modal attention-based multi-modal fusion in social networks;Computers and Electrical Engineering;2024-08

3. Prompt-based mental health screening from social media text;Anais do XIII Brazilian Workshop on Social Network Analysis and Mining (BraSNAM 2024);2024-07-21

4. BERT-based RNN for Effective Detection of Depression with Severity Levels from Text Data;2024 IEEE Symposium on Wireless Technology & Applications (ISWTA);2024-07-20

5. The use of machine learning and deep learning models in detecting depression on social media: A systematic literature review;Personalized Medicine in Psychiatry;2024-07

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