Psychological Counseling and Personality Analysis Algorithm Simulation Based on Deep Learning

In this study, data collection and preprocessing were carried out first. Various forms of psychological data were collected, including text, audio, video, etc. Subsequently, pre-processing of data cleaning and sentiment analysis was performed to ensure data quality and availability. Secondly, convolutional neural network is selected and designed as a deep learning model. Then, the model is trained and verified. The model is trained and evaluated effectively by dividing data set, extracting features, training and verifying the model. Finally, the model is optimized and the parameters are adjusted. In summary, this study provides a comprehensive simulation for psychological counseling and personality analysis algorithms based on deep learning, and provides an important reference for research and application in related fields.