SleepDepNet: Reddit Text for Sleep and Depression Analysis

A dataset supporting the SleepDepNet multi-task learning framework, introduced by Akshi Kumar and last updated on 2026-05-07. The data consists of user-generated text collected from Reddit communities related to sleep and mental health. It is used to model the relationship between sleep quality and depressive sentiment.

Use Cases

• Classifying sleep quality from user text based on linguistic patterns mentioned in the description
• Analyzing depressive sentiment in online discourse based on emotion-aware features
• Calculating a unified SleepDepScore for combined risk assessment based on integrated model outputs
• Training interpretable models using attention mechanisms to highlight salient linguistic indicators

Strengths

• Model performance is reported with specific F1-scores: 0.89 for sleep quality and 0.86 for depressive sentiment
• Data is licensed under CC-BY-4.0, allowing for open reuse and modification
• The framework is designed for scalable analysis of online discourse

Limitations

• Row count is unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download
• The dataset is very small at 5.5 KB, indicating limited scope

Provenance

Source

User-generated text from Reddit communities related to sleep and mental health.

Collection Method

Data collected from online discourse, as described for the SleepDepNet framework.

Time Range

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Freshness

Last updated 2026-05-07 17:37:11; freshness should be verified

Geography

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