A Review of Approaches for Identification of Apparent Personality Using Machine or Deep Learning Models - Amit Garg (International Journal of Intelligent Systems and Applications in Engineering, 2024)
The automatic identification of personality has drawn a lot of interest recently and has been the subject of numerous studies using a variety of approaches, modalities, and strategies. A person’s personality can be inferred from their facial expressions, voice samples, comments, and status on social media platforms, questionnaire based interviews, body language, or any other medical approach that can detect the pattern of feelings and behavior of an individual. In general, actual personality detection is a very broad and diverse theme. With the growth in user specific data and AI techniques, while working with various datasets for regression or classification, a variety of machine learning and deep learning techniques have become more common. Also, numerous writers have demonstrated through their experimental setups that non-linguistic clues like body posture and facial expressions, as well as language cues like speech and social media data may be used to study an individual’s personality with a decent amount of accuracy. The primary focus of this study is on computational approaches based on machine learning and deep learning for the given job.