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Depression detection via a Chinese social media platform: a novel causal relation-aware deep learning approach

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Abstract

Depression detection on social media aims to analyze users’ tendency to depression and provide help for the early detection of depressed users. However, most previous research focusses on diagnoses using the binary classification of the English language. Relevant studies focusing on Chinese social media are scarce, although the Chinese language has numerous users, making such detection more necessary for Chinese social media platforms. Hence, based on online review corpus containing rich depression contexts, this research explores fine-grained polarities and causes of depression with weighted graph-RoBERTa neural network, a novel deep-learning model integrating a Chinese-oriented pre-training model and graph convolution architecture. Meanwhile, a causal relationship model is implemented based on the causal inference theory, which proves the interpretability of the proposed approach on the Weibo dataset. The experimental results show that our model outperforms some state-of-the-art baseline models and achieves 75.3% (F1-micro) and 71.8% (F1-macro) in depression polarity, an average of 85.4% (F1-score) and 97.7% (AUC) in cause-detection tasks. In addition, the results of an ablation study demonstrate the effectiveness of all proposed modules. Our work has multiple implications for depression detection in social media, showing the potential application in other mental health conditions.

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  1. https://www.twitter.com/.

  2. https://www.facebook.com/.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 72204190), the Youth Fund for Humanities and Social Science Foundation of the Ministry of Education of China (No. 22YJZH114), China Postdoctoral Science Foundation (No. 2022M722476), Scientific research project of the National Language Commission of China (No. YB145-74).

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  1. School of Information Management, Wuhan University, Wuhan, 430072, China

    Yang Liu

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The authors confirm contribution to the paper as follows: study conception and design, analysis and interpretation of results: Yang Liu. draft manuscript preparation: Yang Liu. All authors reviewed the results and approved the final version of the manuscript.

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Liu, Y. Depression detection via a Chinese social media platform: a novel causal relation-aware deep learning approach. J Supercomput 80, 10327–10356 (2024). https://doi.org/10.1007/s11227-023-05830-y

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