What does this research mean for the field?

MentalBERT outperforms CNN and LSTM models in classifying depression-related content on social media, achieving an F1 score of 0.918 and AUC of 0.962. Novelty: ClaimNovelty.NOVEL_FINDING. Consensus alignment: ConsensusAlignment.NEUTRAL.

March 7, 2026International Journal of Advanced Computer Science and ApplicationsOpen Access

Comparative Analysis of Neural Network Architectures for Classifying Depressive Content in Social Networks

View Full Paper

Ask AI

Bookmark

Authors

YAYntymak AbdrazakhAhmet Yesevi University RIRita Ismailova NZNurseit Zhunissov

Discussion

Member takes

Implication

This research benchmarks neural network models for classifying depressive content in social media, highlighting implications for mental health monitoring.

Key Points

The research aims to evaluate various neural network architectures for classifying depressive content on social media platforms.
Aggregated 19,800 English posts/comments from Reddit, Twitter, and Facebook
Evaluated CNN, LSTM, and transformer models with consistent preprocessing
Applied two evaluation protocols: fixed-split baseline and five-seed repeated-run
Measured performance with metrics like F1 score, AUC, training time, and inference latency
MentalBERT achieved the highest performance with F1 = 0.918 and AUC = 0.962
CNN and LSTM show lower robustness in cross-platform evaluations
Identified significant performance drops when shifting between domains
Reported practical implications for model selection in mental health applications

Cite This Study

Abdrazakh et al. (2026) studied this question.

synapsesocial.com/papers/69abc1645af8044f7a4e9f41 https://doi.org/10.14569/ijacsa.2026.0170237

View Full Paper

Ask AI

Bookmark

Implication

This research benchmarks neural network models for classifying depressive content in social media, highlighting implications for mental health monitoring.

Comparative Analysis of Neural Network Architectures for Classifying Depressive Content in Social Networks

Discussion

Member takes

Implication

Key Points

Cite This Study

Comparative Analysis of Neural Network Architectures for Classifying Depressive Content in Social Networks

Discussion

Member takes

Implication

Key Points

Cite This Study

Also Consider

Also Consider