Reddit Posts for Schizophrenia Language Classification via BERT

31,278 Reddit posts form a balanced dataset with 15,639 posts each from individuals with schizophrenia and control subjects. The dataset was created by J. V. Miranda e Silva to investigate linguistic markers of schizophrenia using a fine-tuned BERT model. It was last updated in April 2026.

Use Cases

• Fine-tune BERT models to classify posts as SZ or control based on textual content.
• Analyze the impact of text length on classification performance, as longer posts (M=37.30 words) were more accurately classified.
• Investigate how discussion topics (e.g., r/Christianity) correlate with model predictions and classification accuracy.
• Study vocabulary choices, particularly words related to mental health conditions, as a feature for distinguishing SZ language.

Strengths

• Balanced dataset containing 15,639 posts per class (SZ and control).
• Model performance metrics are provided (Accuracy=0.6969, AUC=0.78).
• Analysis identifies three concrete factors affecting performance: text length, topic, and vocabulary.

Limitations

• Dataset scope is limited to 31,278 posts from a single platform (Reddit).
• Model performance is moderate (69.69% accuracy), indicating classification challenges.
• Potential geographic and demographic bias inherent to Reddit user data.

Provenance

Source

Reddit posts, compiled by author J. V. Miranda e Silva.

Collection Method

Posts were collected and labeled for a study on schizophrenia language classification.

Freshness

Data was last updated in April 2026.