@inproceedings{5aba8ecbc5bb4ff3b59e25d500f6f59c,
title = "What Symptoms and How Long? An Interpretable AI Approach for Depression Detection in Social Media",
abstract = "Depression is the most prevalent and serious mental illness, which induces grave financial and societal ramifications. Depression detection is key for early intervention to mitigate those consequences. Such a high-stake decision inherently necessitates interpretability. Although a few depression detection studies attempt to explain the decision, these explanations misalign with the clinical depression diagnosis criterion that is based on depressive symptoms. To fill this gap, we develop a novel Multi-Scale Temporal Prototype Network (MSTPNet). MSTPNet innovatively detects and interprets depressive symptoms as well as how long they last. Extensive empirical analyses show that MSTPNet outperforms state-of-the-art depression detection methods. This result also reveals new symptoms that are unnoted in the survey approach. We further conduct a user study to demonstrate its superiority over the benchmarks in interpretability. This study contributes to IS literature with a novel interpretable deep learning model for depression detection in social media.",
keywords = "depression detection, interpretability, multi-scale, prototype learning, social media",
author = "Junwei Kuang and Jiaheng Xie and Zhijun Yan",
note = "Publisher Copyright: {\textcopyright} 2023 International Conference on Information Systems, ICIS 2023: {"}Rising like a Phoenix: Emerging from the Pandemic and Reshaping Hu. All Rights Reserved.; 44th International Conference on Information Systems: Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies, ICIS 2023 ; Conference date: 10-12-2023 Through 13-12-2023",
year = "2023",
language = "English",
series = "International Conference on Information Systems, ICIS 2023: {"}Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies{"}",
publisher = "Association for Information Systems",
booktitle = "International Conference on Information Systems, ICIS 2023",
address = "United States",
}
