This July 2025 research article investigates the use of Large Language Model (LLM) embeddings to predict Big Five personality traits using data from Reddit. The study demonstrates that custom-trained deep learning models using these embeddings significantly outperform zero-shot inference and traditional linguistic feature engineering. Through psychometric validation, the authors confirm that these numerical representations capture essential psycholinguistic and emotional markers, proving their reliability for psychological assessment. A comparison of architectures shows that while OpenAI's proprietary models offer the highest accuracy, open-source alternatives like RoBERTa provide a cost-effective and highly capable substitute. Ultimately, the paper suggests that AI-driven embeddings provide a robust, scalable framework for understanding human personality through natural language. Source: July 8 2025 Psychometric Evaluation of Large Language Model Embeddings for Personality Trait Prediction Kent State University Julina Maharjan, Ruoming Jin, Jianfeng Zhu, Deric Kenne https://www.jmir.org