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Mental disease detection (MDD) from social media has suffered from poorgeneralizability and interpretability, due to lack of symptom modeling. Thispaper introduces PsySym, the first annotated symptom identification corpus ofmultiple psychiatric disorders, to facilitate further research progress. PsySymis annotated according to a knowledge graph of the 38 symptom classes relatedto 7 mental diseases complied from established clinical manuals and scales, anda novel annotation framework for diversity and quality. Experiments show thatsymptom-assisted MDD enabled by PsySym can outperform strong pure-textbaselines. We also exhibit the convincing MDD explanations provided by symptompredictions with case studies, and point to their further potentialapplications.

Symptom Identification for Interpretable Detection of Multiple Mental Disorders