Multifeature Fusion Attention Network for Suicide Risk Assessment Based on Social Media: Algorithm Development and Validation.

We found that bidirectional long short-term memory performs well for long text representation, and the attention mechanism can identify the key information in the text. The external features can complete the semantic information lost by the neural network during feature extraction and further improve the performance of the model. The experimental results showed that our model performs better than the state-of-the-art method. Our work has theoretical and practical value for suicidal risk assessment.