Personality and Sentiment Prediction Using Graphology and Facial Expression

Abstract—Understanding human behavior is a complex and multifaceted endeavor that finds applications in various domains, from psychology to human-computer interaction. Graphology, the study of handwriting, has been associated with personality assessment. It posits that various aspects of a person's character, such as their emotional stability, creativity, and even hidden emotions, are reflected in the way they write. Alternative, facial expression analysis is a well-established field that examines the emotions conveyed through facial movement. By leveraging the strengths of both modalities, this approach aims to improve accuracy and robustness in predicting human behavior. Experimental validation demonstrates the effectiveness of the proposed hybrid model, showcasing its potential applications in areas like mental health assessment, human-computer interaction, and personalized user experiences. Ethical considerations and privacy safeguards are paramount in the handling of personal data, and informed consent is obtained from all participants in accordance with best practices. This study offers a promising methodology for holistic personality and emotion analysis, with implications on fields where understanding human behavior is crucial.