Weibo User Depression Detection: Large-Scale Chinese Social Media Data

This large-scale dataset contains Weibo user activity data for depression detection, published by aidenwang9867 in 2026. It provides a collection of social media records specifically curated to identify mental health indicators within the Chinese linguistic and cultural context.

Use Cases

• Binary classification of Weibo users into depressed or non-depressed categories using post text
• Linguistic feature extraction to identify markers of depression in Chinese social media content
• Sentiment analysis of user-generated posts to track emotional variance over time

Strengths

• Large-scale record count as indicated by the author
• Platform-specific focus on Weibo for Chinese-language NLP
• Targeted labels for depression detection tasks

Limitations

• Unknown exact row count and file size
• Lack of detailed column descriptions in the primary repository
• Potential for label noise common in social media mental health datasets

Provenance

Source

aidenwang9867 via GitHub

Collection Method

Extracted from the Weibo social media platform

Freshness

Last updated March 2026.

Geography

China